R. Alghamdi, N. Saeed, H. Dahrouj, M. Alouini and T. Y. Al-Naffouri

"Towards Ultra-Reliable Low-Latency Underwater Optical Wireless Communications",  in 2019 IEEE 90th Vehicular Technology Conference, Sep 2019. [abstract] [.bib]


The superiority of optical communications in underwater mediums, in terms of higher data rate and reliability, makes underwater optical wireless communications (UOWC) more favorable to provide ultra-reliable low-latency underwater communications, as compared to other wireless technologies, e.g., acoustic and radio frequency (RF) communications. UOWC limited transmission range, however, remains a major hurdle against assessing its true deployment benefits, which motivates for the necessity of developing practical routing protocols for multi-hop underwater optical wireless sensor networks (UOWSNs). This paper sheds light on the existing state-of-art UOWC routing protocols, the majority of which requires centralized implementation with large end-to-end delay. The article further proposes routing algorithms which can be implemented in a distributed fashion across the multi-hop links, with a reasonable amount of information exchange. The merits of the proposed algorithms are particularly highlighted through illustrative simulations, which show how the proposed strategies outperform the classical protocols, both in terms of reliability and end-to-end latency. Finally, the paper shows how the proposed distributive routing protocols achieve ultra-reliable low-latency underwater communications.

Keywords: routing protocols;underwater acoustic communication;underwater optical wireless communication;underwater optical wireless communications;multihop underwater optical wireless sensor networks;end-to-end delay;multihop links;distributive routing protocols;ultra-reliable low-latency underwater communications;UOWC limited transmission range;UOWC routing protocols;UOWSN;information exchange;Routing protocols;Optical scattering;Bit error rate;Oceans;Adaptive optics;Wireless communication;Optical fiber communication

A. A. Ahmad et al

"Rate Splitting and Common Message Decoding for MIMO C-RAN Systems",  in 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, July 2019. [abstract] [.bib]


In this paper, we study the benefits of rate-splitting (RS) in multiple-input multiple-output (MIMO) cloud radio access networks (C-RAN). For this setting, we propose a stream-based transmission scheme in which user's messages are divided into a private and a common part, each of which is encoded into multiple streams. Under this stream-based strategy, we formulate a weighted sum-rate maximization problem subject to backhaul capacity and transmit power constraints. We determine the beamforming vectors of private and common streams of this non-convex optimization problem via a proposed iterative algorithm based on the fractional programming (FP) framework. Numerical results show gains of up to 27% of RS-MIMO over the baseline scheme of treating interference as noise (TIN). Particularly, at large backhaul capacities and specific antenna settings at which interference levels are maximal, rate splitting along with common message decoding is a viable option for effective interference management in MIMO C-RAN.

Keywords: array signal processing;convex programming;decoding;iterative methods;MIMO communication;radio access networks;radiofrequency interference;common message decoding;MIMO C-RAN systems;rate-splitting;multiple-input multiple-output cloud radio access networks;stream-based transmission scheme;multiple streams;stream-based strategy;weighted sum-rate maximization problem;backhaul capacity;transmit power constraints;private streams;common streams;nonconvex optimization problem;fractional programming framework;RS-MIMO;iterative algorithm;beamforming vectors

H. Chen, T. Ballal, X. Liu and T. Y. Al-Naffouri

"Realtime 2-D DOA Estimation using Phase-Difference Projection (PDP)",  in 2019 27th European Signal Processing Conference,  2019. [abstract] [.bib]


Estimating the direction of arrival (DOA) information of a signal is important for communications, localization and navigation systems. Time-delay based methods are popular DOA algorithms that can estimate DOA with a minimal number of receivers. Time delay can be measured with subsample accuracy using phase-difference based methods. Phase-wrapping represents a major challenge for time delay estimation that occurs when inter-sensor spacing is large. Several methods exist for phase-unwrapping; the most successful methods are those search methods, which are time-consuming and do not lend themselves to theoretical analysis. In this paper, we present a phase-difference projection (PDP) method for DOA estimation which is capable of delivering more accurate results with reduced computational complexity. The proposed method has been tested and compared with several benchmark algorithms in both simulations and experiments. The results show that, at a signal-to-noise ratio (SNR) of -18 dB, using the proposed PDP algorithm, the percentage of the DOA estimates with errors smaller than <; 5° is 54%, and it reaches 100% at SNR = -7dB. This performance is not matched by the benchmark methods. For the utility test, we implemented this algorithm to realize an ultrasound-based air-mouse and it achieves satisfactory user experiences when using Google Maps, or playing some interactive games.

Keywords: computational complexity;delay estimation;direction-of-arrival estimation;realtime 2-d;DOA estimation;direction of arrival;localization;navigation systems;time-delay;popular DOA algorithms;phase-difference based methods;phase-wrapping;time delay estimation;inter-sensor spacing;phase-unwrapping;search methods;phase-difference projection method;benchmark algorithms;signal-to-noise ratio;PDP algorithm;benchmark methods;noise figure -18.0 dB;noise figure 7.0 dB

A. Celik, N. Saeed, B. Shihada, T. Y. Al-Naffouri and M. Alouini

"SectOR: Sector-Based Opportunistic Routing Protocol for Underwater Optical Wireless Networks",  in 2019 IEEE Wireless Communications and Networking Conference,  2019. [abstract] [.bib]


Underwater optical wireless communications (UOWC) is an emerging technology to provide underwater applications with high speed and low latency connections. However, it suffers from limited range and requires effective multi-hop routing solutions for the proper operation of underwater optical wireless networks (UOWNs). In this regard, this paper proposes a distributed Sector-based Opportunistic Routing (SectOR) protocol. Unlike the traditional routing techniques which unicast packets to a unique relay, opportunistic routing (OR) targets a set of candidate relays by leveraging the broadcast nature of the UOWC channel. OR is especially suitable for UOWNs as the link connectivity can be disrupted easily due to the underwater channel impairments (e.g., pointing errors, misalignment, turbulence, etc.) and sea creatures passing through the transceivers' line-of-sight. In such cases, OR improves the packet delivery ratio as the likelihood of having at least one successful packet reception is much higher than that in conventional unicast routing. Contingent upon the performance characterization of a single-hop link, we obtain distance progress (DP) and expected (DP) metrics to evaluate the fitness of a candidate set (CS) and prioritize the members of a CS. Since rate↔error and range↔beamwidth tradeoffs yield different candidate set diversities, we develop a candidate selection and prioritization (CSPA) algorithm to find the optimal sector shaped coverage region by scanning the feasible search space. Moreover, a hybrid acoustic/optic coordination mechanism is considered to avoid duplicate transmission of the relays. Numerical results show that SectOR protocol can perform even better than an optimal unicast routing protocol in well-connected UOWNs.

Keywords: telecommunication network reliability;telecommunication network routing;underwater acoustic communication;wireless sensor networks;low latency connections;effective multihop routing solutions;underwater optical wireless networks;distributed Sector-based Opportunistic Routing;traditional routing techniques;unicast packets;candidate relays;UOWC channel;link connectivity;underwater channel impairments;packet delivery ratio;packet reception;conventional unicast routing;single-hop link;candidate selection;optimal sector;SectOR protocol;optimal unicast routing protocol;well-connected UOWNs;optical wireless communications;Routing protocols;Routing;High-speed optical techniques;Optical transmitters;Optical fiber networks;Optical sensors;Transceivers

Xing Liu, Tarig Ballal and T. Y. Al-Naffouri,

"GNSS Ambiguity Resolution and Attitude Determination by Leveraging Relative Baseline and Frequency Information",  in Proceedings of the 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018), Sep 2018. [abstract] [.bib]


Attitude determination is an important application of Global Navigation Satellite Systems (GNSS). However, before GNSS attitude determination can be achieved, the carrier-phase integer ambiguity must be resolved. We handle the attitude determination problem by arranging the GNSS receiving antennas on two non-collinear baselines, which allow us to obtain the 3-D attitude of the moving platform on which they are stationed. Initially, we tackle the ambiguity resolution problem independently over each baseline based on single phase-difference measurements. To this end, we discuss and test two different approaches to carrier-phase ambiguity resolution. We either exploit the receiver antenna configuration or employ multiple carrier frequencies. Namely, we show that for special configurations of collinear antenna triplets, the ambiguity resolution problem can be handled using a simple algebraic formula. A similar approach is developed for a baseline with only two antennas in which we utilize a pair of GNSS carrier frequencies that satisfy a specific condition. The initial solution to the algebraic formula yields only coarse vectors indicating the pointing direction of the baselines and coarse unwrapped phase-difference measurements. Therefore, we develop and apply refining procedures to improve the initial results. Using the obtained coarse phase differences, we formulate the attitude determination problem as a least-squares problem with dual baseline length constraints and an inter-baseline angle constraint. This is a non-convex optimization problem to which we propose an efficient solution. This solution, combined with each of the two ambiguity resolution approaches, results in two different methods for attitude determination. The proposed methods are extensively tested using simulations covering a broad range of scenarios. The results demonstrate high success rates of ambiguity resolution and high attitude accuracy. Moreover, the proposed methods perform reasonably well even in scenarios with a small number of visible satellites.

[161] Ayed M. Alrashdi,Abla Kammoun, Ismail Ben Atitallah, Tarig Ballal, Christos Thrampoulidis, Anas Chaaban and Tareq Y. Al-Naffouri "Optimum Training for Massive MIMO BPSK Transmission",  in 19th IEEE SPAWC international workshop on signal processing advances in wireless communications, Jun 2018. [abstract] [.bib]


In this paper, we derive an analytical expression for the bit error rate (BER) of binary phase shift keying (BPSK) symbols transmitted over a multiple-input multiple-output (MIMO) system. In this wireless communications system, the receiver uses the linear minimum mean squared error (LMMSE) estimator to estimate the channel matrix. The error in this estimation affects the following estimation that is used to recover the transmitted symbols.
We derive the BER of the estimated symbols as a function of the energy allocation. Exploiting the large dimensionality of the problem, we leverage tools from random matrix theory (RMT) to express the BER only in terms of the deterministic parameters of the system.
We further utilize the deterministic expression to find the optimal energy allocation. 
The theoretical results are matched with simulations showing high level
of congruence.

[160] Nasir Saeed, Abdulkadir Celik, Tareq Y. Al-Naffouri and Mohamed-Slim Alouini, "Robust 3D Underwater Optical Wireless Sensor Networks Localization via Low Rank Matrix Completion",  in 19th IEEE SPAWC international workshop on signal processing advances in wireless communications, Jun 2018. [.bib]
[159] N. Saeed, A. Celik, T. Y. Al-Naffouri and M. S. Alouini "Connectivity Analysis of Underwater Optical Wireless Sensor Networks: A Graph Theoretic Approach",  in 2018 IEEE International Conference on Communications Workshops (ICC Workshops), May 2018. [abstract] [.bib]


As an alternative to low rate and high latency acoustic systems, underwater optical wireless sensor network (UOWSN) is a promising technology to enable high speed and low latency underwater communications. However, the aquatic medium poses significant challenges for underwater optical wireless communications (UOWC) such as higher absorption, scattering, ambient noise, and turbulence impairments of seawater. These severe impairments yield very limited transmission ranges and necessitate multihop transmissions to expand communication ranges and enhance the network connectivity. Therefore, one needs to take some crucial design parameters into account in order to achieve a fully connected multihop UOWSN (MH-UOWSN). Unlike the omnidirectional wireless network, one of the most distinctive features of UOWSN is transmission occurs only within a directed beam sector. Therefore, we model an MH-UOWSN as a randomly scaled sector graph where connection among the nodes is established by point-to-point directed links. Thereafter, the probability of network connectivity is analytically derived as a function of communication range, network density, and beam-width. Throughout the extensive simulations, we demonstrate that the probability of an obscured/isolated node strongly depends on these three parameters and the upper bound for network connectivity is achieved at larger beam-widths and dense deployments. The proposed work provides a practical method for effective selection of the physical layer design parameters of MH- UOWSNs.

Keywords: Absorption;High-speed optical techniques;Optical sensors;Optical transmitters;Scattering;Spread spectrum communication;Wireless sensor networks
[158] Y. N. Shnaiwer and Sameh Sorour and T. Y. Al-Naffouri and S. ALGhadhban "Cross-Layer Cloud Offloading using Fog Radio Access Networks and Network Coding",  in IEEE ICC Workshops 2018, May 2018. [.bib]
[157] M. A. Suliman, H. Sifaou, T. Ballal, M. -S. Alouini, and T. Y. Al-Naffouri "Robust Estimation in Linear Ill-posed Problems with Adaptive Regularization Schem",  in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Apr 2018. [.bib]
[156] Mohammed H. Alsharif, Mohamed Saad, Mohamed Siala, Hatem Boujemaa, Tarig Ballal and Tareq Y. Al-Naffouri "High Accuracy Acoustic Estimation of Multiple Targets",  in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, April 2018. [abstract] [.bib]


This paper presents a new adaptation of a Gaussian echo model (GEM) to estimate the distances to multiple targets using acoustic signals. The proposed algorithm utilizes m-sequences and opens the door for applying other modulations and signal designs for acoustic estimation in a similar way. The proposed algorithm estimates the system impulse response and uses the GEM to limit the effect of noise before applying deconvolution to estimate the time of arrival (TOA) to multiple targets with high accuracy. The algorithm was experimentally evaluated for different scenarios with active (transmitters) and passive (reflectors) targets at proximity. In the case of closely spaced static passive targets, results show that 90$%$ of the ranging errors are below 7 mm. When tracking two moving active targets approaching very close proximity, results show that 90$%$ of the ranging errors are less than 10 mm.

[155] Nasir Saeed, Abdulkadir Celik, Tareq Y. Al-Naffouri, and Mohamed-Slim Alouini "Underwater Optical Sensor Networks Localization With Limited Connectivity",  in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Apr 2018. [abstract] [.bib]


In this paper, a received signal strength (RSS) based local-ization technique is investigated for underwater optical wire-less sensor networks (UOWSNs) where optical noise sources (e.g., sunlight, background, thermal, and dark current) and channel impairments of seawater (e.g., absorption, scattering, and turbulence) pose significant challenges. Hence, we pro-pose a localization technique that works on the noisy ranging measurements embedded in a higher dimensional space and localize the sensor network in a low dimensional space. Once the neighborhood information is measured, a weighted net-work graph is constructed, which contains the one-hop neigh-bor distance estimations. A novel approach is developed to complete the missing distances in the kernel matrix. The out-put of the proposed technique is fused with Helmert trans-formation to refine the final location estimation with the help of anchors. The simulation results show that the root means square positioning error (RMSPE) of the proposed technique is more robust and accurate compared to baseline and mani-fold regularization.

[154] A. Celik, N. Saeed, T. Y. Al-Naffouri and Mohamed-Slim Alouini "Modeling and Performance Analysis of Multihop Underwater Optical Wireless Sensor Networks",  in 2018 IEEE Wireless Communications and Networking Conference (WCNC), April 2018. [abstract] [.bib]


Underwater optical wireless networks (UOWNs) have recently gained attention as an emerging solution to the growing demand for broadband connectivity. Even though it is an alternative to low-bandwidth and high-latency acoustic systems, underwater optical wireless communications (UOWC) suffers from limited range and requires effective multi-hop solutions. Therefore, this paper analyzes and compares the performance of multihop underwater optical wireless networks under two relaying schemes: Decode & Forward (DF) and Amplify & Forward (AF). Noting that nodes close to the surface sink (SS) are required to relay more information, these nodes are enabled for retro-reflective communication, where SS illuminates these nodes with a continuous-wave beam which is then modulated and reflected back to the SS receivers. Accordingly, we analytically evaluate important performance metrics including end-to-end bit error rate, achievable multihop data rates, and communication ranges between node pairs. Thereafter, we develop routing algorithms for DF and AF schemes in order to maximize the end-to-end performance metrics. Numerical results demonstrate that multi-hop transmission can significantly enhance the network performance and expand the communication range.

Keywords: amplify and forward communication;decode and forward communication;underwater optical wireless communication;wireless sensor networks;SS receivers;broadband connectivity;end-to-end bit error rate;high-latency acoustic systems;multihop transmission;multihop underwater optical wireless networks;multihop underwater optical wireless sensor networks;retro-reflective communication;underwater optical wireless communications;Adaptive optics;Optical fiber networks;Optical receivers;Optical sensors;Optical transmitters;Spread spectrum communication

Muhammad Moinuddin and Tareq Y. Al-Nafffouri and Khaled A. Al-Hujaili

"Improved Steady State Analysis Of The Recursive Least Squares Algorithm",  in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings,  2018. [abstract] [.bib]


This paper presents a new approach for studying the steady state performance of the Recursive Least Square (RLS) adaptive filter for a circularly correlated Gaussian input. Earlier methods have two major drawbacks: (1) The energy relation developed for the RLS is approximate (as we show later) and (2) The evaluation of the moment of the random variable ||u_i||^2_(P_i) , where u_i is input to the RLS filter and Pi is the estimate of the inverse of input covariance matrix by assuming that u_i and P_i are independent (which is not true). These assumptions could result in negative value of the stead-state Excess Mean Square Error (EMSE). To overcome these issues, we modify the energy relation without imposing any approximation. 
Based on modified energy relation, we derive the steady-state EMSE and two upper bounds on the EMSE. For that, we derive closed from expression for the aforementioned moment which is based on finding the cumulative distribution function (CDF) of the random variable of the form (gamma+||u||^2_D)^-1 where u is correlated circular Gaussian input and D is a diagonal matrix. Simulation results corroborate our analytical findings.

Calgary, Canada

O. M. Bushnaq, A. Celik, H. ElSawy, M. Alouini and T. Y. Al-Naffouri

"Aerial Data Aggregation in IoT Networks: Hovering & Traveling Time Dilemma",  in 2018 IEEE Global Communications Conference,  2018. [abstract] [.bib]


The next era of information revolution will rely on aggregating big data from massive numbers of devices that are widely scattered in our environment. The majority of these devices are expected to be of low-complexity, low-cost, and limited power supply, which impose stringent constraints on the network operation. In this regards, this paper proposes aerial data aggregation from a finite spatial field via an unmanned aerial vehicle (UAV). Instead of fusing, relaying, and routing the data across the wireless nodes to fixed locations access points, an UAV flies over the field and collects the required data. Particularly, the field is divided into several subregions over which the UAV hovers to collect samples from the underlying nodes. To this end, an optimization problem is formulated and solved to find the optimal number of subregions, the area of each subregion, the hovering locations, the hovering time at each location, and the trajectory traversed between hovering locations such that an average number of samples are collected from the field in minimal time. The proposed formulation is shown to be np-hard mixed integer problem, and hence, a decoupled heuristic solution is proposed. The results show that there exists an optimal number of subregions that balance the tradeoff between hovering and traveling times such that the total time for collecting the required samples is minimized.

Keywords: autonomous aerial vehicles;Big Data;computational complexity;data aggregation;integer programming;Internet of Things;aerial data aggregation;unmanned aerial vehicle;fixed locations access points;UAV hovers;hovering locations;hovering traveling times;IoT networks;big data;hovering time dilemma;traveling time dilemma;optimization problem;NP-hard mixed integer problem;Drones;Data aggregation;Interference;Wireless communication;Optimization;Signal to noise ratio;Unmanned aerial vehicle (UAV);Internet of things (IoT);stochastic geometry;coverage problem;travel salesman

M. Emara, H. ElSawy, S. Sorour, S. Al-Ghadhban, M. Alouini and T. Y. Al-Naffouri

"Flexible Design of Millimeter-Wave Cache Enabled Fog Networks",  in IEEE Globecom Workshops,  2018. [abstract] [.bib]


Ultra-densification, millimeter wave (mmW) communications, and proactive network-edge caching, utilized within mmW fog networks (mmFNs), are foreseen to provide tangible gains for broadband access, network capacity, and latency. However, caching implementation in mmFN imposes high capital expenditure (CAPEX) due to the ultra-high density of base stations (BSs). For a given caching CAPEX, it may be more efficient to install higher capacity caches in a fraction of the BSs than installing smaller capacity caches in every BSs. In the former case, wireless self-backhauling of mmW systems can be exploited to share the cache contents stored in a given cache enabled BSs (CE-BSs) with other BSs in the network. In this regards, this paper develops a mathematical model, based on stochastic geometry, to study the tradeoff between the cache size and intensity of CE-BSs on the probability that requested popular contents are retrieved from the network edge, denoted as the hit probability. Assuming a power-law inverse relationship between the cache size and intensity of CE-BSs, an optimization problem is formulated and solved for the intensity of CE-BSs and probabilistic file placement in caches such that the hit probability is maximized. The results show that neither installing small caches in every BS nor having sufficiently high capacity caches (i.e., that confine all popular files) installed in small number of BSs exploit the full potential of mmFN. Instead, there exists an optimal balance between the cache size and intensity of CE-BSs, which depends on the network parameters such as the applied caching strategy, required rate, total intensity of BSs, popular content distribution, and cache size/intensity relationship.

Keywords: cache storage;peer-to-peer computing;probability;millimeter-wave cache;millimeter wave communications;proactive network-edge caching;network capacity;caching implementation;cache contents;network edge;network parameters;applied caching strategy;fog networks;cache size-intensity relationship;high capacity caches;capacity caches;caching CAPEX;base stations;content distribution;Antenna arrays;Probabilistic logic;Geometry;Cellular networks;Broadband communication;Wireless communication;Stochastic processes;Caching System;Stochastic Geometry;mmW;self-backhauling;ultra-dense networks

H. Chen, T. Ballal and T. Y. Al-Naffouri

"FAST PHASE-DIFFERENCE-BASED DOA ESTIMATION USING RANDOM FERNS",  in 2018 IEEE Global Conference on Signal and Information Processing,  2018. [abstract] [.bib]


Direction of arrival (DOA) information of a signal is important in communications, localization, object tracking and so on. Frequency-domain-based time-delay estimation is capable of achieving DOA in subsample accuracy; however, it suffers from the phase wrapping problem. In this paper, a frequency-diversity based method is proposed to overcome the phase wrapping problem. Inspired by the machine learning technique of random ferns, an algorithm is proposed to speed up the search procedure. The performance of the algorithm is evaluated based on three different signal models using both simulations and experimental tests. The results show that using random ferns can reduce search time to 1/6 of the search time of the exhaustive method while maintaining the same accuracy. The proposed search approach outperforms a benchmark frequency-diversity based algorithm by offering lower DOA estimation error.

Keywords: delay estimation;direction-of-arrival estimation;frequency-domain analysis;learning (artificial intelligence);object tracking;search problems;fast phase-difference-based DOA estimation;random ferns;object tracking;frequency-domain-based time-delay estimation;subsample accuracy;phase wrapping problem;frequency-diversity based method;machine learning technique;search procedure;search time;benchmark frequency-diversity based algorithm;signal models;DOA estimation error;Direction-of-arrival estimation;Estimation;Mathematical model;Entropy;Sensors;Frequency estimation;Time-frequency analysis;Direction of Arrival;Random Ferns;Machine Learning;Ultrasound;Phase-difference

M. A. Suliman, T. Ballal, M. H. AlSharif, M. Saad and T. Y. Al-Naffouri

"Robust 3-D Location Estimation in the Presence of Anchor Placement and Range Errors",  in 2018 15th Workshop on Positioning, Navigation and Communications,  2018. [abstract] [.bib]


This paper addresses the problem of 3-D location estimation from perturbed range information and uncertain anchor positions. The 3-D location estimation problem is formulated as a min-max convex optimization problem with a set of second-order cone constraints. Robust optimization tools are applied to convert these cone constrains to semi-definite programming constraints and achieve robust location estimation without prior knowledge of the statistical distributions of the errors. Simulation results demonstrate the superiority of the proposed approach over other benchmark algorithms in a wide range of measurement error scenarios.

Keywords: convex programming;measurement errors;minimax techniques;navigation;parameter estimation;radionavigation;sensor placement;statistical distributions;wireless sensor networks;second-order cone constraints;robust optimization tools;cone constrains;semidefinite programming constraints;robust location estimation;measurement error scenarios;robust 3-D location estimation;perturbed range information;uncertain anchor positions;3-D location estimation problem;min-max convex optimization problem;range errors;anchor placement;3-D location estimation;matrix uncertainty;robust convex optimization

M. A. Suliman, T. Ballal, M. H. AlSharif, M. Saad and T. Y. Al-Naffouri

"Joint Scheduling and Beamforming via Cloud-Radio Access Networks Coordination",  in 2018 15th Workshop on Positioning, Navigation and Communications,  2018. [abstract] [.bib]


This paper addresses the problem of 3-D location estimation from perturbed range information and uncertain anchor positions. The 3-D location estimation problem is formulated as a min-max convex optimization problem with a set of second-order cone constraints. Robust optimization tools are applied to convert these cone constrains to semi-definite programming constraints and achieve robust location estimation without prior knowledge of the statistical distributions of the errors. Simulation results demonstrate the superiority of the proposed approach over other benchmark algorithms in a wide range of measurement error scenarios.

Keywords: convex programming;measurement errors;minimax techniques;navigation;parameter estimation;radionavigation;sensor placement;statistical distributions;wireless sensor networks;second-order cone constraints;robust optimization tools;cone constrains;semidefinite programming constraints;robust location estimation;measurement error scenarios;robust 3-D location estimation;perturbed range information;uncertain anchor positions;3-D location estimation problem;min-max convex optimization problem;range errors;anchor placement;3-D location estimation;matrix uncertainty;robust convex optimization

X. Yang, K. Elkhalil, A. Kammoun, T. Y. Al-Naffouri and M. Alouini

"Regularized Discriminant Analysis: A Large Dimensional Study",  in 2018 IEEE International Symposium on Information Theory,  2018. [abstract] [.bib]


This paper focuses on studying the performance of general regularized discriminant analysis (RDA) classifiers based on the Gaussian mixture model with different means and covariances. RDA offers a rich class of regularization options, covering as special cases the regularized linear discriminant analysis (RLDA) and the regularized quadratic discriminant analysis (RQDA) classifiers. Based on fundamental results from random matrix theory, we analyze RDA under the double asymptotic regime where the data dimension and the training size both increase in a proportional way. Under the double asymptotic regime and some mild assumptions, we show that the asymptotic classification error converges to a deterministic quantity that only depends on the data statistical parameters and dimensions. This result can be leveraged to select the optimal parameters that minimize the classification error, thus yielding the optimal classifier. Numerical results are provided to validate our theoretical findings on synthetic data showing high accuracy of our derivations.

Keywords: covariance matrices;Gaussian processes;mixture models;pattern classification;random matrix theory;RDA;double asymptotic regime;data dimension;asymptotic classification error;data statistical parameters;optimal classifier;general regularized discriminant analysis classifiers;Gaussian mixture model;covariances;regularization options;regularized linear discriminant analysis;regularized quadratic discriminant analysis classifiers;deterministic quantity

O. Dhifallah, H. Dahrouj, T. Y. Al-Naffouri and M. Alouini

"Robust Beamforming for Cache-Enabled Cloud Radio Access Networks",  in 2018 IEEE Globecom Workshops,  2018. [abstract] [.bib]


Popular content caching is expected to play a major role in efficiently reducing backhaul congestion and achieving user satisfaction in next generation mobile radio systems. Consider the downlink of a cache-enabled cloud radio access network (CRAN), where each cache-enabled base-station (BS) is equipped with limited-size local cache storage. The central computing unit (cloud) is connected to the BSs via capacity-limited backhaul links and serves a set of single-antenna mobile users (MUs). This paper assumes that only imperfect channel state information (CSI) is available at the cloud. The paper then focuses on the problem of minimizing the total network power and backhaul cost so as to determine the beamforming vector of each user across the network, and the quantization noise covariance matrix across the backhaul links, subject to imperfect channel state information, per-BS power constraint, and fixed cache placement assumption. The paper proposes solving such a difficult, non-convex ℓ0-norm-based optimization problem using the semi-definite relaxation (SDR) and the S-procedure methods. The paper first uses a fine-tuned ℓ0-norm approximation so as to find the surrogate function that majorizes the cost function. It then provides a stationary point to the problem using the majorization-minimization (MM) approach. Simulation results show the convergence of the proposed algorithm and highlight how the cache-enabled network significantly improves the backhaul cost as compared to conventional cache-less CRANs, especially at high signal-to-interference-plus-noise ratio (SINR) values.

Keywords: array signal processing;cache storage;cloud computing;concave programming;covariance matrices;mobile radio;radio access networks;cache-enabled cloud radio access network;popular content caching;backhaul congestion;cache-enabled base-station;limited-size local cache storage;central computing unit;backhaul links;imperfect channel state information;total network power;backhaul cost;fixed cache placement assumption;cache-enabled network;user satisfaction;conventional cache-less CRAN;next generation mobile radio systems;covariance matrix;semidefinite relaxation;majorization-minimization approach;Array signal processing;Quantization (signal);Interference;Power demand;Covariance matrices;Optimization;Signal to noise ratio

Mostafa Emara and Hesham Elsawy and Sameh Sorour and Samir Al-Ghadhban and Mohamed-Slim Alouini and Tareq Y. Al-Naffouri

"Optimal Caching in Multicast 5G Networks with Opportunistic Spectrum Access",  in IEEE Global Communications Conference GLOBECOM 2017, Dec 2017. [.bib]
[144] K. Elkhalil and A. Kammoun and R. Couillet and T. Y. Al-Naffouri and M. S. Alouini "Asymptotic performance of regularized quadratic discriminant analysis based classifiers",  in 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP), Sep 2017. [abstract] [.bib]

Abstract This paper carries out a large dimensional analysis of the standard regularized quadratic discriminant analysis (QDA) classifier designed on the assumption that data arise from a Gaussian mixture model. The analysis relies on fundamental results from random matrix theory (RMT) when both the number of features and the cardinality of the training data within each class grow large at the same pace. Under some mild assumptions, we show that the asymptotic classification error converges to a deterministic quantity that depends only on the covariances and means associated with each class as well as the problem dimensions. Such a result permits a better understanding of the performance of regularized QDA and can be used to determine the optimal regularization parameter that minimizes the misclassification error probability. Despite being valid only for Gaussian data, our theoretical findings are shown to yield a high accuracy in predicting the performances achieved with real data sets drawn from popular real data bases, thereby making an interesting connection between theory and practice.

Keywords: Gaussian processes;feature extraction;matrix algebra;optimisation;pattern classification;probability;Gaussian mixture model;RMT;asymptotic classification error;asymptotic performance;dimensional analysis;misclassification error probability;optimal regularization parameter;random matrix theory;regularized QDA;regularized quadratic discriminant analysis based classifiers;training data;Convergence;Covariance matrices;Error analysis;Gaussian distribution;Random variables;Standards;Training;QDA;classification;deterministic equivalent;machine learning;random matrix theory

Y. Shnaiwer and S. Sorour and P. Sadeghi and T.Y. Al-Naffouri,

"Online Cloud Offloading using Heterogenous Enhanced Remote Radio Heads",  in IEEE Vehicular Technology Conference (VTC’17-Fall), Sep 2017. [.bib]
[142] O. M. Bushnaq and T. Y. Al-Naffouri and S. P. Chepuri and G. Leus "Joint sensor placement and power rating selection in energy harvesting wireless sensor networks",  in 2017 25th European Signal Processing Conference (EUSIPCO), Aug 2017. [abstract] [.bib]

Abstract In this paper, the focus is on optimal sensor placement and power rating selection for parameter estimation in wireless sensor networks (WSNs). We take into account theamount of energy harvested by the sensing nodes, communication link quality, and the observation accuracy at the sensor level. In particular, the aim is to reconstruct the estimationparameter with minimum error at a fusion center under a system budget constraint. To achieve this goal, a subset of sensing locations is selected from a large pool of candidate sensinglocations. Furthermore, the type of sensor to be placed at those locations is selected from a given set of sensor types (e.g., sensors with different power ratings). We furtherinvestigate whether it is better to install a large number of cheap sensors, a few expensive sensors or a combination of different sensor types at the optimal locations.

Keywords: Batteries;Covariance matrices;Europe;Optimization;Sensors;Signal processing;Wireless sensor networks;Wireless sensor networks;convex optimization;energyharvesting;estimation;sensor selection
[141] A. M. Alanazi and T. Ballal and M. Masood and T. Y. Al-Naffouri "Image deblurring using a perturbation-basec regularization approach",  in 2017 25th European Signal Processing Conference (EUSIPCO), Aug 2017. [abstract] [.bib]

Abstract The image restoration problem deals with images in which information has been degraded by blur or noise. In this work, we present a new method for image deblurring by solvinga regularized linear least-squares problem. In the proposed method, a synthetic perturbation matrix with a bounded norm is forced into the discrete ill-conditioned model matrix. Thisperturbation is added to enhance the singular-value structure of the matrix and hence to provide an improved solution. A method is proposed to find a near-optimal value of theregularization parameter for the proposed approach. To reduce the computational complexity, we present a technique based on the bootstrapping method to estimate the regularizationparameter for both low and high-resolution images. Experimental results on the image deblurring problem are presented. Comparisons are made with three benchmark methods and the resultsdemonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and SSIM values.

Keywords: Computational complexity;Computational modeling;Europe;Image restoration;Mathematical model;Signal processing;Signal processing algorithms;Bootstrapping;Tikhonovregularization;bounded perturbation regularization;image deblurring;linear least-squares problems
[140] H. Chen , T. Ballal , M. Saad and T. Y. Al-Naffouri "Angle-of-arrival-based gesture recognition using ultrasonic multi-frequency signals",  in 2017 25th European Signal Processing Conference (EUSIPCO), Aug 2017. [abstract] [.bib]


Hand gestures are tools for conveying information, expressing emotion, interacting with electronic devices or even serving disabled people as a second language. A gesture canbe recognized by capturing the movement of the hand, in real time, and classifying the collected data. Several commercial products such as Microsoft Kinect, Leap Motion Sensor,Synertial Gloves and HTC Vive have been released and new solutions have been proposed by researchers to handle this task. These systems are mainly based on optical measurements,inertial measurements, ultrasound signals and radio signals. This paper proposes an ultrasonic-based gesture recognition system using AOA (Angle of Arrival) information of ultrasonicsignals emitted from a wearable ultrasound transducer. The 2-D angles of the moving hand are estimated using multi-frequency signals captured by a fixed receiver array. A simpleredundant dictionary matching classifier is designed to recognize gestures representing the numbers from â€ک0’ to â€ک9’ and compared with a neural network classifier. Averageclassification accuracies of 95.5% and 94.4% are obtained, respectively, using the two classification methods.

Keywords: Acoustics;Dictionaries;Estimation;Europe;Gesture recognition;Receivers;Signal processing
[139] M. H. AlSharif , M. Saad , M. Siala , T. Ballal , H. Boujemaa and T. Y. Al-Naffouri "Zadoff-Chu coded ultrasonic signal for accurate range estimation",  in 2017 25th European Signal Processing Conference (EUSIPCO), Aug 2017. [abstract] [.bib]


This paper presents a new adaptation of Zadoff-Chu sequences for the purpose of range estimation and movement tracking. The proposed method uses Zadoff-Chu sequencesutilizing a wideband ultrasonic signal to estimate the range between two devices with very high accuracy and high update rate. This range estimation method is based on time of flight(TOF) estimation using cyclic cross correlation. The system was experimentally evaluated under different noise levels and multi-user interference scenarios. For a single user, theresults show less than 7 mm error for 90% of range estimates in a typical indoor environment. Under the interference from three other users, the 90% error was less than 25 mm. Thesystem provides high estimation update rate allowing accurate tracking of objects moving with high speed.

Keywords: Acoustics;Correlation;Distance measurement;Estimation;Interference;Signal processing;Wideband
[138] Ayed Alrashdi and Ismail Ben AtitallahIsmail and Tareq Y. Al-Naffouri and Mohamed-Slim Alouini "Precise Performance analysis of the LASSO under Matrix Uncertainty",  in 5th IEEE Global Conference on Signal and Information Processing (GlobalSip 2017), Jul 2017. [.bib]

Tarig Ballal and Mohamed Suliman and Tareq Y. AlNaffouri

"Near-optimal parameter selection methods for l2 regularization",  in 5th IEEE Global Conference on Signal and Information Processing (GlobalSip 2017), Jul 2017. [abstract] [.bib]


This paper focuses on the problem of selecting the regularization parameter for linear least-squares estimation. Usually, the problem is formulated as a minimization problem with a cost function consisting of the square sum of the l 2 norm of the residual error, plus a penalty term of the squared norm of the solution multiplied by a constant. The penalty term has the effect of shrinking the solution towards the origin with magnitude that depends on the value of the penalty constant. By considering both squared and non-squared norms of the residual error and the solution, four different cost functions can be formed to achieve the same goal. In this paper, we show that all the four cost functions lead to the same closed-form solution involving a regularization parameter, which is related to the penalty constant through a different constraint equation for each cost function. We show that for three of the cost functions, a specific procedure can be applied to combine the constraint equation with the mean squared error (MSE) criterion to develop approximately optimal regularization parameter selection algorithms. Performance of the developed algorithms is compared to existing methods to show that the proposed algorithms stay closest to the optimal MSE.

[136] S. J. Lin and A. Alloum and T. Al-naffouri "Principal pivot transforms on radix-2 DFT-type matrices",  in 2017 IEEE International Symposium on Information Theory (ISIT), Jun 2017. [abstract] [.bib]

Abstract In this paper, we discuss the principal pivot transforms (PPT) on a family of matrices, called the radix-2 DFT-type matrices. Given a transformation matrix, the PPT of thematrix is a transformation matrix with exchanging some entries between the input array and the output array. The radix-2 DFT-type matrices form a classification of matrices such thatthe transformations by the matrices can be calculated via radix-2 butterflies. A number of well-known matrices, such as radix-2 DFT matrices and Hadamard matrices, belong to thisclassification. In this paper, the sufficient conditions for the PPTs on radix-2 DFT-type matrices are given, such that their transformations can also be computed in O{n lg n). Thenbased on the results above, an encoding algorithm for systematic Reed-Solomon (RS) codes in O{n lg n) field operations is presented.

Keywords: Hadamard matrices;Reed-Solomon codes;discrete Fourier transforms;Hadamard matrices;PPT;Reed-Solomon codes;principal pivot transforms;radix-2 DFT-type matrices;radix-2butterflies;transformation matrix;Discrete Fourier transforms;Electronic mail;Encoding;Error correction;Linear systems
[135] I. Ben Atitallah and C. Thrampoulidis and A. Kammoun and T. Y. Al-Naffouri and M. S. Alouini and B. Hassibi "The BOX-LASSO with application to GSSK modulation in massive MIMO systems",  in 2017 IEEE International Symposium on Information Theory (ISIT), Jun 2017. [abstract] [.bib]

Abstract The BOX-LASSO is a variant of the popular LASSO that includes an additional box-constraint. We propose its use as a decoder in modern Multiple Input Multiple Output (MIMO)communication systems with modulation methods such as the Generalized Space Shift Keying (GSSK) modulation, which produces constellation vectors that are inherently sparse and withbounded elements. In that direction, we prove novel explicit asymptotic characterizations of the squared-error and of the per-element error rate of the BOX-LASSO, under iid Gaussianmeasurements. In particular, the theoretical predictions can be used to quantify the improved performance of the BOX-LASSO, when compared to the previously used standard LASSO. Weinclude simulation results that validate both these premises and our theoretical predictions.

Keywords: MIMO communication;modulation;signal denoising;vectors;BOX-LASSO;GSSK modulation;basis pursuit denoising;bounded elements;constellation vectors;explicit asymptoticsquared-error characterizations;generalized space shift keying modulation;iid Gaussian measurements;massive MIMO systems;per-element error rate;Atmosphericmeasurements;Decoding;MIMO;Modulation;Noise measurement;Standards
[134] M. Emara and H. ElSawy and S. Sorour and S. Al-Ghadhban and M. S. Alouini and T. Y. Al-Naffouri "Stochastic geometry model for multi-channel fog radio access networks",  in 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), May 2017. [abstract] [.bib]

Abstract Cache-enabled base station (BS) densification, denoted as a fog radio access network (F-RAN), is foreseen as a key component of 5G cellular networks. F-RAN enables storingpopular files at the network edge (i.e., BS caches), which empowers local communication and alleviates traffic congestions at the core/backhaul network. The hitting probability, whichis the probability of successfully transmitting popular files request from the network edge, is a fundamental key performance indicator (KPI) for F-RAN. This paper develops ascheduling aware mathematical framework, based on stochastic geometry, to characterize the hitting probability of F-RAN in a multi-channel environment. To this end, we assess andcompare the performance of two caching distribution schemes, namely, uniform caching and Zipf caching. The numerical results show that the commonly used single channel environmentleads to pessimistic assessment for the hitting probability of F-RAN. Furthermore, the numerical results manifest the superiority of the Zipf caching scheme and quantify the hittingprobability gains in terms of the number of channels and cache size.

Keywords: 5G mobile communication;cellular radio;radio access networks;stochastic processes;5G cellular networks;F-RAN;cache-enabled base station densification;multichannel fog radioaccess networks;scheduling aware mathematical framework;stochastic geometry model;Cellular networks;Conferences;Geometry;Interference;Mathematical model;Numerical models;Stochasticprocesses;Caching system;F-RAN;Multichannel;Stochastic geometry
[133] M. Behzad and M. Masood and T. Ballal and M. Shadaydeh and T. Y. Al-Naffouri "Image denoising via collaborative support-agnostic recovery",  in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2017. [abstract] [.bib]

Abstract In this paper, we propose a novel patch-based image denoising algorithm using collaborative support-agnostic sparse reconstruction. In the proposed collaborative scheme,similar patches are assumed to share the same support taps. For sparse reconstruction, the likelihood of a tap being active in a patch is computed and refined through a collaborationprocess with other similar patches in the similarity group. This provides a very good patch support estimation, hence enhancing the quality of image restoration. Performancecomparisons with state-of-the-art algorithms, in terms of PSNR and SSIM, demonstrate the superiority of the proposed algorithm.

Keywords: estimation theory;groupware;image denoising;image restoration;PSNR;SSIM;collaborative support-agnostic recovery;collaborative support-agnostic sparse reconstruction;imagerestoration;patch support estimation;patch-based image denoising;Collaboration;Computational complexity;Dictionaries;Estimation;Image denoising;Noise reduction;Signal to noiseratio;PSNR;SSIM;collaborative estimation;image denoising;similar patches;sparse reconstruction
[132] I. Ben Atitallah and C. Thrampoulidis and A. Kammoun and T. Y. Al-Naffouri and B. Hassibi and M. S. Alouini "BER analysis of regularized least squares for BPSK recovery",  in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2017. [abstract] [.bib]

Abstract This paper investigates the problem of recovering an n-dimensional BPSK signal x0 ∈ {-1, 1

Keywords: Gaussian processes;decoding;error statistics;least mean squares methods;phase shift keying;vectors;BER analysis;BPSK recovery;MMSE detector;binary phase shift keying;biterror probability;bit error rate;box relaxation;convex relaxation;m-dimensional measurement vector;n-dimensional BPSK signal;regularized least squares;Binary phase shift keying;Biterror rate;Closed-form solutions;Decoding;Detectors;Error probability;Signal to noise ratio;BER analysis;MMSE;box relaxation;high dimensions;regularized least squares
[131] R. Arshad and H. ElSawy and S. Sorour and T. Y. Al-Naffouri and M. S. Alouini "Cooperative Handover Management in Dense Cellular Networks",  in 2016 IEEE Global Communications Conference (GLOBECOM), Dec 2016. [abstract] [.bib]

Abstract Network densification has always been an important factor to cope with the ever increasing capacity demand. Deploying more base stations (BSs) improves the spatial frequencyutilization, which increases the network capacity. However, such improvement comes at the expense of shrinking the BSs' footprints, which increases the handover (HO) rate and maydiminish the foreseen capacity gains. In this paper, we propose a cooperative HO management scheme to mitigate the HO effect on throughput gains achieved via cellular networkdensification. The proposed HO scheme relies on skipping HO to the nearest BS at some instances along the user's trajectory while enabling cooperative BS service during HO execution atother instances. To this end, we develop a mathematical model, via stochastic geometry, to quantify the performance of the proposed HO scheme in terms of coverage probability and userthroughput. The results show that the proposed cooperative HO scheme outperforms the always best connected based association at high mobility. Also, the value of BS cooperation alongwith handover skipping is quantified with respect to the HO skipping only that has recently appeared in the literature. Particularly, the proposed cooperative HO scheme showsthroughput gains of 12% to 27% and 17% on average, when compared to the always best connected and HO skipping only schemes at user velocity ranging from 80 km/h to 160 Km/h,respectively.

Keywords: cellular radio;cooperative communication;mobility management (mobile radio);probability;stochastic processes;base station;best connected based association;cellular networkdensification;cooperative BS service;cooperative HO management scheme;cooperative handover management;coverage probability;handover skipping;mathematical model;network capacityincrement;spatial frequency utilization improvement;stochastic geometry;throughput gain;user throughput;Cellular networks;Handover;Interference;Signal to noiseratio;Throughput;Trajectory
[130] M. E. Eltayeb , T. Y. Al-Naffouri and R. W. Heath "Compressive Sensing for Blockage Detection in Vehicular Millimeter Wave Antenna Arrays",  in 2016 IEEE Global Communications Conference (GLOBECOM), Dec 2016. [abstract] [.bib]


The radiation pattern of an antenna array depends on the excitation weights and the geometry of the array. Due to mobility, some vehicular antenna elements might be subjectedto full or partial blockages from a plethora of particles like dirt, salt, ice, and water droplets. These particles cause absorption and scattering to the signal incident on the array,and as a result, change the array geometry. This distorts the radiation pattern of the array mostly with an increase in the sidelobe level and decrease in gain. In this paper, wepropose a blockage detection technique for millimeter wave vehicular antenna arrays that jointly estimates the locations of the blocked antennas and the attenuation and phase-shiftsthat result from the suspended particles. The proposed technique does not require the antenna array to be physically removed from the vehicle and permits real-time array diagnosis.Numerical results show that the proposed technique provides satisfactory results in terms of block detection with low detection time provided that the number of blockages is smallcompared to the array size.

Keywords: antenna radiation patterns;compressed sensing;millimetre wave antenna arrays;absorption;array geometry;blockage detection;compressive sensing;radiation pattern;real-timearray diagnosis;scattering;vehicular antenna elements;vehicular millimeter wave antenna arrays;Absorption;Antenna arrays;Antenna measurements;Antenna radiation patterns;Compressedsensing;Scattering
[129] O. Dhifallah and H. Dahrouj and T. Y. Al-Naffouri and M. S. Alouini "Distributed Robust Power Minimization for the Downlink of Multi-Cloud Radio Access Networks",  in 2016 IEEE Global Communications Conference (GLOBECOM), Dec 2016. [abstract] [.bib]


Conventional cloud radio access networks assume single cloud processing and treat inter-cloud interference as background noise. This paper considers the downlink of amulti-cloud radio access network (CRAN) where each cloud is connected to several base-stations (BS) through limited-capacity wireline backhaul links. The set of BSs connected to eachcloud, called cluster, serves a set of pre-known mobile users (MUs). The performance of the system becomes therefore a function of both inter-cloud and intra-cloud interference, aswell as the compression schemes of the limited capacity backhaul links. The paper assumes independent compression scheme and imperfect channel state information (CSI) where the CSIerrors belong to an ellipsoidal bounded region. The problem of interest becomes the one of minimizing the network total transmit power subject to BS power and quality of serviceconstraints, as well as backhaul capacity and CSI error constraints. The paper suggests solving the problem using the alternating direction method of multipliers (ADMM). One of thehighlight of the paper is that the proposed ADMM-based algorithm can be implemented in a distributed fashion across the multi-cloud network by allowing a limited amount of informationexchange between the coupled clouds. Simulation results show that the proposed distributed algorithm provides a similar performance to the centralized algorithm in a reasonable numberof iterations.

Keywords: cloud computing;distributed algorithms;minimisation;quality of service;radio access networks;radio links;radiofrequency interference;telecommunicationcomputing;telecommunication power management;wireless channels;ADMM-based algorithm;CRAN downlink;CSI error constraints;alternating direction method of multipliers;backgroundnoise;base-stations;cloud processing;distributed algorithm;distributed robust power minimization;ellipsoidal bounded region;imperfect CSI;imperfect channel stateinformation;information exchange;inter-cloud interference;intra-cloud interference;limited capacity backhaul link compression;limited-capacity wireline backhaul links;mobileusers;multicloud radio access networks downlink;quality of service constraints;system performance;total transmit power minimization;Array signal processing;Distributedalgorithms;Downlink;Interference;Minimization;Optimization;Quantization (signal)
[128] K. Elkhalil and A. Kammoun and T. Y. Al-Naffouri and M. S. Alouini "A Blind Antenna Selection Scheme for Single-Cell Uplink Massive MIMO",  in 2016 IEEE Globecom Workshops (GC Wkshps), Dec 2016. [abstract] [.bib]

Abstract This paper considers the uplink of a single-cell large-scale multiple-input multiple output (MIMO) system in which m mono-antenna users communicate with a base station (BS)outfitted by n antennas. We assume that the number of antennas at the BS and that of users take large values, as envisioned by large-scale MIMO systems. This allows for high spectralefficiency gains but obviously comes at the cost of higher complexity, a fact that becomes all the more critical as the number of antennas grows large. To solve this issue is to choosea subset of the available n antennas. The subset must be carefully chosen to achieve the best performance. However, finding the optimal subset of antennas is usually a difficult task,requiring one to solve a high dimensional combinatorial optimization problem. In this paper, we approach this problem in two ways. The first one consists in solving a convex relaxationof the problem using standard convex optimization tools. The second technique solves the problem using a greedy approach. The main advantages of the greedy approach lies in its widerscope, in that, unlike the first approach, it can be applied irrespective of the considered performance criterion. As an outcome of this feature, we show that the greedy approach canbe applied even when only the channel statistics are available at the BS, which provides blind way to perform antenna selection.

Keywords: MIMO communication;antenna arrays;cellular radio;combinatorial mathematics;convex programming;greedy algorithms;statistical analysis;wireless channels;base station;blindantenna selection scheme;channel statistics;convex relaxation;dimensional combinatorial optimization problem;greedy approach;large-scale MIMO systems;mono-antenna users;performancecriterion;single-cell uplink massive MIMO system;single-cell uplink massive multiple-input multiple output system;spectral efficiency gains;standard convex optimizationtools;Complexity theory;Greedy algorithms;MIMO;Measurement;Receiving antennas;Uplink
[127] M. Suliman and T. Ballal and T. Y. Al-Naffouri "Robust regularized least-squares beamforming approach to signal estimation",  in 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Dec 2016. [abstract] [.bib]

Abstract In this paper, we address the problem of robust adaptive beamforming of signals received by a linear array. The challenge associated with the beamforming problem is twofold.Firstly, the process requires the inversion of the usually ill-conditioned covariance matrix of the received signals. Secondly, the steering vector pertaining to the direction ofarrival of the signal of interest is not known precisely. To tackle these two challenges, the standard capon beamformer is manipulated to a form where the beamformer output is obtainedas a scaled version of the inner product of two vectors. The two vectors are linearly related to the steering vector and the received signal snapshot, respectively. The linearoperator, in both cases, is the square root of the covariance matrix. A regularized least-squares (RLS) approach is proposed to estimate these two vectors and to provide robustnesswithout exploiting prior information. Simulation results show that the RLS beamformer using the proposed regularization algorithm outperforms state-of-the-art beamforming algorithms,as well as another RLS beamformers using a standard regularization approaches.

Keywords: array signal processing;covariance matrices;direction-of-arrival estimation;least squares approximations;vectors;RLS beamformer;adaptive beamforming;covariancematrix;direction of arrival;linear array;robust regularized least-squares beamforming approach;signal estimation;signal snapshot;standard capon beamformer;standard regularizationapproaches;steering vector;Array signal processing;Covariance matrices;Eigenvalues and eigenfunctions;Linear systems;Robustness;STEM;Uncertainty;Capon beamformer;Robustbeamforming;adaptive beamforming;regularized least-squares

Mohammed Eltayeb and Tareq Al-Naffouri and Robert Heath

"Compressive Sensing for Vehicular Millimeter Wave Antenna Array Diagnosis",  in IEEE Global Communications Conference (GLOBECOM), Dec 2016. [.bib]
[125] B. Al-Oquibi and O. Amin and H. Dahrouj and T. Y. Al-Naffouri and M. S. Alouini "Energy efficiency for cloud-radio access networks with imperfect channel state information",  in 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Sep 2016. [abstract] [.bib]

Abstract The advent of smartphones and tablets over the past several years has resulted in a drastic increase of global carbon footprint, due to the explosive growth of data traffic.Improving energy efficiency (EE) becomes, therefore, a crucial design metric in next generation wireless systems (5G). Cloud radio access network (C-RAN), a promising 5G networkarchitecture, provides an efficient framework for improving the EE performance, by means of coordinating the transmission across the network. This paper considers a C-RAN system formedby several clusters of remote radio heads (RRHs), each serving a predetermined set of mobile users (MUs), and assumes imperfect channel state information (CSI). The network performancebecomes therefore a function of the intra-cluster and inter-cluster interference, as well as the channel estimation error. The paper optimizes the transmit power of each RRH in orderto maximize the network global EE subject to MU service rate requirements and RRHs maximum power constraints. The paper proposes solving the optimization problem using a heuristicalgorithm based on techniques from optimization theory via a two-stage iterative solution. Simulation results show that the proposed power allocation algorithm provides an appreciableperformance improvement as compared to the conventional systems with maximum power transmission strategy. They further highlight the convergence of the proposed algorithm for differentnetworks scenarios.

Keywords: 5G mobile communication;channel estimation;cloud computing;energy conservation;radio access networks;radiofrequency interference;telecommunication powermanagement;telecommunication traffic;5G network architecture;C-RAN system;channel estimation error;cloud radio access network;cloud-radio access networks;data traffic;energyefficiency;global carbon footprint;heuristic algorithm;imperfect channel state information;inter-cluster interference;intra-cluster interference;mobile users;next generation wirelesssystems;remote radio heads;smartphones;tablets;5G mobile communication;Channel estimation;Estimation error;Interference;Optimization;Resource management
[124] S. J. Lin and A. Alloum and T. Y. Al-Naffouri "RAID-6 reed-solomon codes with asymptotically optimal arithmetic complexities",  in 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Sep 2016. [abstract] [.bib]

Abstract In computer storage, RAID 6 is a level of RAID that can tolerate two failed drives. When RAID-6 is implemented by Reed-Solomon (RS) codes, the penalty of the writingperformance is on the field multiplications in the second parity. In this paper, we present a configuration of the factors of the second-parity formula, such that the arithmeticcomplexity can reach the optimal complexity bound when the code length approaches infinity. In the proposed approach, the intermediate data used for the first parity is also utilizedto calculate the second parity. To the best of our knowledge, this is the first approach supporting the RAID-6 RS codes to approach the optimal arithmetic complexity.

Keywords: Reed-Solomon codes;computational complexity;RAID-6 Reed-Solomon codes;RS codes;asymptotic optimal arithmetic complexity;code length;field multiplications;optimal complexitybound;second-parity formula;Complexity theory;Decoding;Electronic mail;Land mobile radio;Reed-Solomon codes;Reflective binary codes;STEM;Distributed storage systems;RAID-6codes;computational complexity;erasure codes
[123] M. E. Eltayeb and J. Choi and T. Y. Al-Naffouri and R. W. Heath "On the Security of Millimeter Wave Vehicular Communication Systems Using Random Antenna Subsets",  in 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), Sep 2016. [abstract] [.bib]

Abstract Millimeter wave (mmWave) vehicular communication systems have the potential to improve traffic efficiency and safety. Lack of secure communication links, however, may lead toa formidable set of abuses and attacks. To secure communication links, a physical layer precoding technique for mmWave vehicular communication systems is proposed in this paper. Theproposed technique exploits the large dimensional antenna arrays available at mmWave systems to produce direction dependent transmission. This results in coherent transmission to thelegitimate receiver and artificial noise that jams eavesdroppers with sensitive receivers. Theoretical and numerical results demonstrate the validity and effectiveness of the proposedtechnique and show that the proposed technique provides high secrecy throughput when compared to conventional array and switched array transmission techniques.

Keywords: jamming;millimetre wave antenna arrays;mobile radio;precoding;telecommunication security;antenna arrays;artificial noise;communication links;eavesdroppers;millimeter wavevehicular communication systems;physical layer precoding technique;random antenna subsets;secrecy throughput;switched array transmission techniques;traffic efficiency;Antennaarrays;Receiving antennas;Security;Signal to noise ratio;Transmitting antennas
[122] M. Suliman and T. Ballal and A. Kammoun and T. Y. Al-Naffouri "Penalized linear regression for discrete ill-posed problems: A hybrid least-squares and mean-squared error approach",  in 2016 24th European Signal Processing Conference (EUSIPCO), Aug 2016. [abstract] [.bib]

Abstract This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificialperturbation matrix with a bounded norm is forced into the discrete ill-posed model matrix. This perturbation is introduced to enhance the singular-value (SV) structure of the matrixand hence to provide a better solution. The proposed approach is derived to select the regularization parameter in a way that minimizes the mean-squared error (MSE) of the estimator.Numerical results demonstrate that the proposed approach outperforms a set of benchmark methods in most cases when applied to different scenarios of discrete ill-posed problems.Jointly, the proposed approach enjoys the lowest run-time and offers the highest level of robustness amongst all the tested methods.

Keywords: least mean squares methods;minimisation;regression analysis;signal processing;singular value decomposition;MSE minimization;SV structure enhancement;artificial perturbationmatrix;hybrid least-square-mean-squared error approach;linear least-square discrete ill-posed problem;linear regression penalization;singular value structure enhancenent;Benchmarktesting;Europe;Indexes;Mathematical model;Periodic structures;STEM;Signal processing;ill-posed problem;linear estimation;linear least-squares;regularization
[121] K. Elkhalil and A. Kammoun and T. Y. Al-Naffouri and M. S. Alouini "Exact closed-form expression for the inverse moments of one-sided correlated Gram matrices",  in 2016 IEEE International Symposium on Information Theory (ISIT), Jul 2016. [abstract] [.bib]

Abstract In this paper, we derive a closed-form expression for the inverse moments of one sided-correlated random Gram matrices. Such a question is mainly motivated by applications insignal processing and wireless communications for which evaluating this quantity is a question of major interest. This is for instance the case of the best linear unbiased estimator,in which the average estimation error corresponds to the first inverse moment of a random Gram matrix.

Keywords: matrix algebra;closed-form expression;estimation error;inverse moments;linear unbiased estimator;one-sided correlated gram matrices;Closed-form solutions;BLUE;Grammatrices;Inverse moments;One-sided correlation;mean square error
[120] K. Elkhalil and M. Eltayeb and A. Kammoun and T. Y. Al-Naffouri and H. R. Bahrami "Block compressed sensing for feedback reduction in relay-aided multiuser full duplex networks",  in 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Jul 2016. [abstract] [.bib]

Abstract Opportunistic user selection is a simple technique that exploits the spatial diversity in multiuser relay-aided networks. Nonetheless, channel state information (CSI) fromall users (and cooperating relays) is generally required at a central node in order to make selection decisions. Practically, CSI acquisition generates a great deal of feedbackoverhead that could result in significant transmission delays. In addition to this, the presence of a full-duplex cooperating relay corrupts the fed back CSI by additive noise and therelay's loop (or self) interference. This could lead to transmission outages if user selection is based on inaccurate feedback information. In this paper, we propose an opportunisticfull-duplex feedback algorithm that tackles the above challenges. We cast the problem of joint user signal-to-noise ratio (SNR) and the relay loop interference estimation at thebase-station as a block sparse signal recovery problem in compressive sensing (CS). Using existing CS block recovery algorithms, the identity of the strong users is obtained and theircorresponding SNRs are estimated. Numerical results show that the proposed technique drastically reduces the feedback overhead and achieves a rate close to that obtained by techniquesthat require dedicated error-free feedback from all users. Numerical results also show that there is a trade-off between the feedback interference and load, and for short coherenceintervals, full-duplex feedback achieves higher throughput when compared to interference-free (half-duplex) feedback.

Keywords: compressed sensing;relay networks (telecommunication);CS block recovery algorithm;CSI;SNR;additive noise;base-station;block compressed sensing;block sparse signalrecovery;channel state information;coherence interval;error-free feedback;feedback overhead;feedback reduction;full-duplex cooperating relay;full-duplex feedbackalgorithm;interference-free feedback;opportunistic user selection;relay loop interference estimation;relay-aided multiuser full duplex network;signal-to-noise ratio;spatialdiversity;transmission outages;Additive noise;Downlink;Estimation;Fading channels;Interference;Relays;Signal to noise ratio;Feedback;compressive sensing;decode-and-forward;full-duplexrelaying;scheduling
[119] I. Ben Atitallah and A. Kammoun and M. S. Alouini and T. Y. Al-Naffouri "Robust adaptive subspace detection in impulsive noise",  in 2016 IEEE Statistical Signal Processing Workshop (SSP), Jun 2016. [abstract] [.bib]

Abstract This paper addresses the design of the Adaptive Subspace Matched Filter (ASMF) detector in the presence of compound Gaussian clutters and a mismatch in the steering vector.In particular, we consider the case wherein the ASMF uses the regularized Tyler estimator (RTE) to estimate the clutter covariance matrix. Under this setting, a major question thatneeds to be addressed concerns the setting of the threshold and the regularization parameter. To answer this question, we consider the regime in which the number of observations usedto estimate the RTE and their dimensions grow large together. Recent results from random matrix theory are then used in order to approximate the false alarm and detection probabilitiesby deterministic quantities. The latter are optimized in order to maximize an upper bound on the asymptotic detection probability while keeping the asymptotic false alarm probabilityat a fixed rate.

Keywords: Gaussian processes;adaptive filters;covariance matrices;impulse noise;matched filters;probability;signal detection;ASMF detector;RTE;adaptive subspace matchedfilter;asymptotic detection probability;asymptotic false alarm probability;clutter covariance matrix;compound Gaussian clutters;impulsive noise;random matrix theory;regularizationparameter;regularized Tyler estimator;robust adaptive subspace detection;steering vector;Clutter;Conferences;Covariance matrices;Detectors;Doppler effect;Signalprocessing;Standards;Random matrix theory;Robust estimation;Subspace detection
[118] A. Alloum , S. J. Lin and T. Y. Al-Naffouri "On locality of Generalized Reed-Muller codes over the broadcast erasure channel",  in 2016 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Jun 2016. [abstract] [.bib]


One to Many communications are expected to be among the killer applications for the currently discussed 5G standard. The usage of coding mechanisms is impacting broadcastingstandard quality, as coding is involved at several levels of the stack, and more specifically at the application layer where Rateless, LDPC, Reed Slomon codes and network codingschemes have been extensively studied, optimized and standardized in the past. Beyond reusing, extending or adapting existing application layer packet coding mechanisms based onprevious schemes and designed for the foregoing LTE or other broadcasting standards; our purpose is to investigate the use of Generalized Reed Muller codes and the value of theirlocality property in their progressive decoding for Broadcast/Multicast communication schemes with real time video delivery. Our results are meant to bring insight into the use oflocally decodable codes in Broadcasting.

Keywords: 5G mobile communication;Reed-Muller codes;Reed-Solomon codes;broadcast channels;broadcast communication;broadcasting;channel coding;decoding;multicast communication;networkcoding;parity check codes;5G standard;LDPC code;LTE;Reed Solomon code;application layer packet coding mechanism;broadcast communication scheme;broadcast erasure channel;broadcastingstandard quality;generalized Reed-Muller code;multicast communication scheme;network coding scheme;progressive decoding;rateless code;real time video delivery;Encoding;Frequencymodulation;Maximum likelihood decoding;Reed-Solomon codes;Standards;Application layer codes;Erasure Channel;Generalized Reed Muller codes;Locally Decodable Codes
[117] A. Douik and H. Dahrouj and T. Y. Al-Naffouri and M. S. Alouini "Resilient backhaul network design using hybrid radio/free-space optical technology",  in 2016 IEEE International Conference on Communications (ICC), May 2016. [abstract] [.bib]

Abstract The radio-frequency (RF) technology is a scalable solution for the backhaul planning. However, its performance is limited in terms of data rate and latency. Free SpaceOptical (FSO) backhaul, on the other hand, offers a higher data rate but is sensitive to weather conditions. To combine the advantages of RF and FSO backhauls, this paper proposes acost-efficient backhaul network using the hybrid RF/FSO technology. To ensure a resilient backhaul, the paper imposes a given degree of redundancy by connecting each node through Klink-disjoint paths so as to cope with potential link failures. Hence, the network planning problem considered in this paper is the one of minimizing the total deployment cost bychoosing the appropriate link type, i.e., either hybrid RF/FSO or optical fiber (OF), between each couple of base-stations while guaranteeing K link-disjoint connections, a data ratetarget, and a reliability threshold. The paper solves the problem using graph theory techniques. It reformulates the problem as a maximum weight clique problem in the planning graph,under a specified realistic assumption about the cost of OF and hybrid RF/FSO links. Simulation results show the cost of the different planning and suggest that the proposed heuristicsolution has a close-to-optimal performance for a significant gain in computation complexity.

Keywords: free-space optical communication;graph theory;optical fibre communication;telecommunication network planning;backhaul planning;computation complexity;cost-efficient backhaulnetwork;data rate target;free space optical backhaul;graph theory;hybrid RF-FSO links;hybrid RF-FSO technology;hybrid radio-free-space optical technology;link-disjoint paths;maximumweight clique problem;network planning problem;optical fiber;radiofrequency technology;reliability threshold;resilient backhaul network design;weather conditions;Joiningprocesses;Optical design;Optical fiber networks;Planning;Radio frequency;Reliability;Backhaul network design;deployment cost minimization;free-space optic;link-disjoint graph;opticalfiber
[116] O. M. S. Al-Ebraheemy and A. Chaaban and T. Y. Al-Naffouri and M. S. Alouini "Capacity bounds for the 2-user Gaussian IM-DD optical multiple-access channel",  in 2016 IEEE International Symposium on Circuits and Systems (ISCAS), May 2016. [abstract] [.bib]

Abstract Optical wireless communications (OWC) is a potential solution for coping with the mismatch between the users growing demand for higher data-rates and the wireless networkcapabilities. In this paper, a multi-user OWC scenario is studied from an in formation-theoretic perspective. The studied network consists of two users communicating simultaneouslywith one access point using OWC, thus establishing an optical uplink channel. The capacity of this network is an important metric which reflects the highest possible communicationrates that can be achieved over this channel. Capacity outer and inner bounds are derived, and are shown to be fairly tight in the high signal-to-noise ratio regime.

Keywords: Gaussian processes;optical fibre networks;2-user Gaussian IM-DD optical multiple access channel;capacity bounds;optical uplink channel;optical wirelesscommunications;wireless network capabilities;Optical receivers;Optical sensors;Optical transmitters;Signal to noise ratio;Silicon carbide;Upper bound
[115] R. Arshad and H. ElSawy and S. Sorour and T. Y. Al-Naffouri and M. S. Alouini "Handover management in dense cellular networks: A stochastic geometry approach",  in 2016 IEEE International Conference on Communications (ICC), May 2016. [abstract] [.bib]

Abstract Cellular operators are continuously densifying their networks to cope with the ever-increasing capacity demand. Furthermore, an extreme densification phase for cellularnetworks is foreseen to fulfill the ambitious fifth generation (5G) performance requirements. Network densification improves spectrum utilization and network capacity by shrinking basestations' (BSs) footprints and reusing the same spectrum more frequently over the spatial domain. However, network densification also increases the handover (HO) rate, which maydiminish the capacity gains for mobile users due to HO delays. In highly dense 5G cellular networks, HO delays may neutralize or even negate the gains offered by network densification.In this paper, we present an analytical paradigm, based on stochastic geometry, to quantify the effect of HO delay on the average user rate in cellular networks. To this end, wepropose a flexible handover scheme to reduce HO delay in case of highly dense cellular networks. This scheme allows skipping the HO procedure with some BSs along users' trajectories.The performance evaluation and testing of this scheme for only single HO skipping shows considerable gains in many practical scenarios.

Keywords: cellular radio;mobility management (mobile radio);5G cellular networks;dense cellular networks;fifth generation;handover management;handover rate;network capacity;networkdensification;performance evaluation;performance testing;shrinking base stations;spectrum utilization;stochastic geometry approach;Delays;Geometry;Handover;Interference;Mobilecommunication;Mobile computing;Trajectory;Dense Cellular Networks;Handover Management;Stochastic Geometry
[114] L. H. Afify and H. ElSawy and T. Y. Al-Naffouri and M. S. Alouini "Unified tractable model for downlink MIMO cellular networks using stochastic geometry",  in 2016 IEEE International Conference on Communications (ICC), May 2016. [abstract] [.bib]

Abstract Several research efforts are invested to develop stochastic geometry models for cellular networks with multiple antenna transmission and reception (MIMO). On one hand, thereare models that target Abstract outage probability and ergodic rate for simplicity. On the other hand, there are models that sacrifice simplicity to target more tangible performancemetrics such as the error probability. Both types of models are completely disjoint in terms of the analytic steps to obtain the performance measures, which makes it challenging toconduct studies that account for different performance metrics. This paper unifies both techniques and proposes a unified stochastic-geometry based mathematical paradigm to account forerror probability, outage probability, and ergodic rates in MIMO cellular networks. The proposed model is also unified in terms of the antenna configurations and leads to simpler errorprobability analysis compared to existing state-of-the-art models. The core part of the analysis is based on Abstracting unnecessary information conveyed within the interfering signalsby assuming Gaussian signaling. To this end, the accuracy of the proposed framework is verified against state-of-the-art models as well as system level simulations. We provide via thisunified study insights on network design by reflecting system parameters effect on different performance metrics.

Keywords: MIMO communication;antenna arrays;cellular radio;error statistics;telecommunication signalling;Gaussian signaling;antenna configurations;downlink MIMO cellularnetworks;ergodic rates;error probability;error probability analysis;interfering signals;multiple antenna reception;multiple antenna transmission;network design;outageprobability;performance metrics;stochastic geometry models;system level simulations;unified tractable model;Analytical models;Errorprobability;Geometry;Interference;MIMO;Precoding;Stochastic processes;MIMO cellular networks;ergodic rate;error probability;outage probability;stochastic geometry
[113] K. A. Al-Hujaili and T. Y. Al-Naffouri and M. Moinuddin "The steady-state of the (Normalized) LMS is schur convex",  in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2016. [abstract] [.bib]

Abstract In this work, we demonstrate how the theory of majorization and schur-convexity can be used to assess the impact of input-spread on the Mean Squares Error (MSE) performanceof adaptive filters. First, we show that the concept of majorization can be utilized to measure the spread in input-regressors and subsequently order the input-regressors according totheir spread. Second, we prove that the MSE of the Least Mean Squares Error (LMS) and Normalized LMS (NLMS) algorithms are schur-convex, that is, the MSE of the LMS and the NLMSalgorithms preserve the majorization order of the inputs which provide an analytical justification to why and how much the MSE performance of the LMS and the NLMS algorithmsdeteriorate as the spread in input increases.

Keywords: adaptive filters;least mean squares methods;regression analysis;NLMS algorithms;Schur-convexity;adaptive filters;input-regressors;least mean squares error;normalized LMSalgorithms;Algorithm design and analysis;Approximation algorithms;Covariance matrices;Eigenvalues and eigenfunctions;Mean square error methods;Simulation;Steady-state;AdaptiveFilters;Majorization;Mean Square Error Analysis;Schur-convexity;input-spread
[112] H. Ali and S. Ahmed and T. Y. Al-Naffouri and M. S. Alouini "Reduced complexity FFT-based DOA and DOD estimation for moving target in bistatic MIMO radar",  in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2016. [abstract] [.bib]

Abstract In this paper, we consider a bistatic multiple-input multiple-output (MIMO) radar. We propose a reduced complexity algorithm to estimate the direction-of-arrival (DOA) anddirection-of-departure (DOD) for moving target. We show that the calculation of parameter estimation can be expressed in terms of one-dimensional fast-Fourier-transforms whichdrastically reduces the complexity of the optimization algorithm. The performance of the proposed algorithm is compared with the two-dimension multiple signal classification (2D-MUSIC)and reduced-dimension MUSIC (RD-MUSIC) algorithms. It is shown by simulations, our proposed algorithm has better estimation performance and lower computational complexity compared tothe 2D-MUSIC and RD-MUSIC algorithms. Moreover, simulation results also show that the proposed algorithm achieves the Cramer-Rao lower bound.

Keywords: MIMO radar;direction-of-arrival estimation;fast Fourier transforms;optimisation;radar signal processing;signal classification;2D-MUSIC algorithms;Crameجپr-Rao lower bound;DOAestimation;DOD estimation;FFT;RD-MUSIC algorithms;bistatic MIMO radar;computational complexity;direction-of-arrival estimation;direction-of-departure estimation;movingtarget;multiple-input multiple-output radar;one-dimensional fast-Fourier-transforms;optimization algorithm;parameter estimation;reduced complexity algorithm;reduced-dimensionMUSIC;two-dimension multiple signal classification;Complexity theory;Direction-of-arrival estimation;Estimation;MIMO radar;Receivers;Transmitters;US Department of Defense;Bistatic MIMOradar;direction of arrival;direction of departure

S. Al-Shuhail and A. Ali and T. AlNaffouri

"Peak-to-average power ratio reduction in interleaved OFDMA systems",  in 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Dec 2015. [abstract] [.bib]


Orthogonal frequency division multiple access (OFDMA) systems suffer from several impairments, and communication system engineers use powerful signal processing tools to combat these impairments and to keep up with the capacity/rate demands. One of these impairments is high peak-to-average power ratio (PAPR) and clipping is the simplest peak reduction scheme. However, in general, when multiple users are subjected to clipping, frequency domain clipping distortions spread over the spectrum of all users. This results in compromised performance and hence clipping distortions need to be mitigated at the receiver. Mitigating these distortions in multiuser case is not simple and requires complex clipping mitigation procedures at the receiver. However, it was observed that interleaved OFDMA presents a special structure that results in only self-inflicted clipping distortions (i.e., the distortions of a particular user do not interfere with other users). In this work, we prove analytically that distortions do not spread over multiple users (while utilizing interleaved carrier assignment in OFDMA) and construct a compressed sensing system that utilizes the sparsity of the clipping distortions and recovers it on each user. We provide numerical results that validate our analysis and show promising performance for the proposed clipping recovery scheme.

Keywords: OFDM modulation;compressed sensing;distortion;frequency division multiple access;frequency-domain analysis;PAPR;compressed sensing system;frequency domain clipping distortions;interleaved OFDMA systems;orthogonal frequency division multiple access system;peak-to-average power ratio reduction scheme;self-inflicted clipping distortions;signal processing tools;Frequency-domain analysis;Nonlinear distortion;Peak to average power ratio;Receivers;Resource management;Time-domain analysis;Compressed Sensing;Interleaved OFDMA;Nonlinear Distortions;PAPR Reduction
[110] A. Douik and S. Sorour and T. Y. Al-Naffouri and M. S. Alouini "Rate Aware Instantly Decodable Network Codes",  in 2015 IEEE Globecom Workshops (GC Wkshps), Dec 2015. [abstract] [.bib]

Abstract This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rateawareness. While most of the existing literature on IDNC does not consider any physical layer complications, this paper proposes a cross-layer scheme that incorporates the differentchannel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The completion time minimizationproblem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of thecompletion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. Further, the paper provides amulti-layer solution to improve the completion time approximation. Simulation results suggest that the cross-layer design largely outperforms the uncoded transmissions strategies andthe classical IDNC scheme.

Keywords: cellular radio;decoding;graph theory;minimisation;network coding;RA-IDNC graph;cellular users;channel rate;completion time approximation;completion time minimizationproblem;cross-layer scheme;decision process;maximum weight clique problem;multilayer solution;physical-layer rate awareness;rate aware IDNC graph;rate aware instantly-decodable networkcodes;transmitted message combination;uncoded transmission strategy;Decoding;Delay effects;Indexes;Network coding;Optimal scheduling;Schedules
[109] Y. N. Shnaiwer and S. Sorour and N. Aboutorab and P. Sadeghi and T. Y. Al-Naffouri "Network-Coded Content Delivery in Femtocaching-Assisted Cellular Networks",  in 2015 IEEE Global Communications Conference (GLOBECOM), Dec 2015. [abstract] [.bib]

Abstract Next-generation cellular networks are expected to be assisted by femtocaches (FCs), which collectively store the most popular files for the clients. Given any arbitrarynon-fragmented placement of such files, a strict no-latency constraint, and clients' prior knowledge, new file download requests could be efficiently handled by both the FCs and themacrocell base station (MBS) using opportunistic network coding (ONC). In this paper, we aim to find the best allocation of coded file downloads to the FCs so as to minimize the MBSinvolvement in this download process. We first formulate this optimization problem over an ONC graph, and show that it is NP-hard. We then propose a greedy approach that maximizes thenumber of files downloaded by the FCs, with the goal to reduce the download share of the MBS. This allocation is performed using a dual conflict ONC graph to avoid conflicts among theFC downloads. Simulations show that our proposed scheme almost achieves the optimal performance and significantly saves on the MBS bandwidth.

Keywords: cache storage;computational complexity;femtocellular radio;graph theory;network coding;next generation networks;optimisation;MBS;NP-hard problem;coded file downloadallocation;download process;download share reduction;dual conflict ONC graph;femtocaching-assisted cellular network;file arbitrary nonfragmented placement;greedy approach;macrocellbase station;network-coded content delivery;new file download request;next-generation cellular network;opportunistic network coding;optimization problem;strict no-latencyconstraint;Bandwidth;Libraries;Macrocell networks;Optimization;Petroleum;Resource management;Wireless communication
[108] T. Y. Al-Naffouri "Efficient channel estimation in massive MIMO systems - a distributed approach",  in 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Dec 2015. [abstract] [.bib]

Abstract We present two efficient algorithms for distributed estimation of channels in massive MIMO systems. The two cases of 1) generic, and 2) sparse channels is considered. Thealgorithms estimate the impulse response for each channel observed by the antennas at the receiver (base station) in a coordinated manner by sharing minimal information amongneighboring antennas. Simulations demonstrate the superior performance of the proposed methods as compared to other methods.

Keywords: MIMO communication;antenna arrays;channel estimation;transient response;MIMO system;channel estimation;generic channels;impulse response;massive MIMO system;sparsechannels;Frequency response;MIMO;OFDM;Wireless communication
[107] A. Douik, H. Dahrouj, T. Y. Al-Naffouri and M. S. Alouini "Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks",  in 2015 IEEE Global Communications Conference (GLOBECOM), Dec 2015. [abstract] [.bib]


In the context of resource allocation in cloud- radio access networks, recent studies assume either signal-level or scheduling-level coordination. This paper, instead,considers a hybrid level of coordination for the scheduling problem in the downlink of a multi-cloud radio- access network, so as to benefit from both scheduling policies. Consider amulti-cloud radio access network, where each cloud is connected to several base-stations (BSs) via high capacity links, and therefore allows joint signal processing between them.Across the multiple clouds, however, only scheduling-level coordination is permitted, as it requires a lower level of backhaul communication. The frame structure of every BS iscomposed of various time/frequency blocks, called power- zones (PZs), and kept at fixed power level. The paper addresses the problem of maximizing a network-wide utility by associatingusers to clouds and scheduling them to the PZs, under the practical constraints that each user is scheduled, at most, to a single cloud, but possibly to many BSs within the cloud, andcan be served by one or more distinct PZs within the BSs' frame. The paper solves the problem using graph theory techniques by constructing the conflict graph. The scheduling problemis, then, shown to be equivalent to a maximum- weight independent set problem in the constructed graph, in which each vertex symbolizes an association of cloud, user, BS and PZ, with aweight representing the utility of that association. Simulation results suggest that the proposed hybrid scheduling strategy provides appreciable gain as compared to thescheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

Keywords: graph theory;radio access networks;resource allocation;signal processing;telecommunication scheduling;BS;PZ;backhaul communication;base station;graph theory technique;hybridscheduling-signal-level coordination network;maximum-weight independent set problem;multicloud radio-access network;power-zone;resource allocation;signal processing;time-frequencyblock;Cloud computing;Downlink;Interference;Joining processes;Optimization;Signal to noise ratio
[106] M. E. Eltayeb and A. Alkhateeb and R. W. Heath and T. Y. Al-Naffouri "Opportunistic beam training with hybrid analog/digital codebooks for mmWave systems",  in 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Dec 2015. [abstract] [.bib]

Abstract Millimeter wave (mmWave) communication is one solution to provide more spectrum than available at lower carrier frequencies. To provide sufficient link budget, mmWave systemswill use beamforming with large antenna arrays at both the transmitter and receiver. Training these large arrays using conventional approaches taken at lower carrier frequencies,however, results in high overhead. In this paper, we propose a beam training algorithm that efficiently designs the beamforming vectors with low training overhead. Exploiting mmWavechannel reciprocity, the proposed algorithm relaxes the need for an explicit feedback channel, and opportunistically terminates the training process when a desired quality of serviceis achieved. To construct the training beamforming vectors, a new multi-resolution codebook is developed for hybrid analog/digital architectures. Simulation results show that theproposed algorithm achieves a comparable rate to that obtained by exhaustive search solutions while requiring lower training overhead when compared to prior work.

Keywords: array signal processing;millimetre wave antenna arrays;millimetre wave propagation;radio networks;exhaustive search solutions;hybrid analog-digital codebooks;large antennaarrays;millimeter wave communication;mmWave channel reciprocity;mmWave systems;opportunistic beam training algorithm;Algorithm design and analysis;Antennas;Array signalprocessing;MIMO;Quality of service;Radio frequency;Training
[105] O. Dhifallah and H. Dahrouj and T. Y. Al-Naffouri and M. S. Alouini "Decentralized Group Sparse Beamforming for Multi-Cloud Radio Access Networks",  in 2015 IEEE Global Communications Conference (GLOBECOM), Dec 2015. [abstract] [.bib]

Abstract Recent studies on cloud-radio access networks (CRANs) assume the availability of a single processor (cloud) capable of managing the entire network performance; inter-cloudinterference is treated as background noise. This paper considers the more practical scenario of the downlink of a CRAN formed by multiple clouds, where each cloud is connected to acluster of multiple-antenna base stations (BSs) via high-capacity wireline backhaul links. The network is composed of several disjoint BSs' clusters, each serving a pre-known set ofsingle-antenna users. To account for both inter- cloud and intra-cloud interference, the paper considers the problem of minimizing the total network power consumption subject toquality of service constraints, by jointly determining the set of active BSs connected to each cloud and the beamforming vectors of every user across the network. The paper solves theproblem using Lagrangian duality theory through a dual decomposition approach, which decouples the problem into multiple and independent subproblems, the solution of which depends onthe dual optimization problem. The solution then proceeds in updating the dual variables and the active set of BSs at each cloud iteratively. The proposed approach leads to adistributed implementation across the multiple clouds through a reasonable exchange of information between adjacent clouds. The paper further proposes a centralized solution to theproblem. Simulation results suggest that the proposed algorithms significantly outperform the conventional per-cloud update solution, especially at high signal-to-interference-plus-noise ratio (SINR) target.

Keywords: antennas;array signal processing;cloud computing;duality (mathematics);optimisation;quality of service;radio access networks;radiofrequency interference;telecommunicationnetwork management;CRANs;Lagrangian duality theory;SINR;adjacent clouds;decentralized group sparse beamforming;dual decomposition approach;dual optimization problem;highsignal-to-interference-plus- noise ratio;high-capacity wireline backhaul links;inter-cloud interference;intra-cloud interference;multicloud radio access networks;multiple-antenna basestations;network performance management;quality of service constraints;single processor;single-antenna users;total network power consumption;Array signal processing;Cloudcomputing;Downlink;Interference;Optimization;Power demand;Signal to noise ratio
[104] O. Hammi and A. Abdelhafiz and F. M. Ghannouchi and T. Y. Al-Naffouri "On the use of compressed sampling algorithms for impairments compensation in dynamic nonlinear transmitters",  in 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Dec 2015. [abstract] [.bib]

Abstract Since its introduction, compressed sampling (CS) has found use in various applications ranging from image restoration, radar and sensing to channel and system identification.Recently in the radio frequency (RF) power amplifier (PA) design and linearization communities, there have been many attempts to utilize the CS technique to enable the development ofefficient wireless transmitters. This paper provides a brief review of the use of CS in PA and transmitter linearization. Mainly two approaches are discussed: the use of CS to recoveramplitude-distorted signals, and the use of CS to reduce the complexity of the digital predistorters. Experimental results obtained using an envelope tracking (ET) PA prototype showthe potential and value of the CS technique in developing efficient predistorters at a low computational cost.

Keywords: compressed sensing;distortion;image restoration;linearisation techniques;radar signal processing;radar transmitters;radio transmitters;radiofrequency power amplifiers;CStechnique;ET PA prototype;RF PA design;amplitude-distorted signals;compressed sampling algorithms;digital predistorters;dynamic nonlinear transmitters;envelope tracking;imagerestoration;impairment compensation;linearization communities;radio frequency power amplifier;transmitter linearization;wireless transmitters;Computational modeling;Mathematicalmodel;Nonlinear distortion;Power amplifiers;Sensors;Sparse matrices;compressed sampling;data-aided estimation;envelope tracking;nonlinear distortion;power amplifiers
[103] O. Dhifallah and H. Dahrouj and T. Y. Al-Naffouri and M. S. Alouini "Joint Hybrid Backhaul and Access Links Design in Cloud-Radio Access Networks",  in 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall), Sep 2015. [abstract] [.bib]

Abstract The cloud-radio access network (CRAN) is expected to be the core network architecture for next generation mobile radio systems. In this paper, we consider the downlink of aCRAN formed of one central processor (the cloud) and several base station (BS), where each BS is connected to the cloud via either a wireless or capacity-limited wireline backhaullink. The paper addresses the joint design of the hybrid backhaul links (i.e., designing the wireline and wireless backhaul connections from the cloud to the BSs) and the access links(i.e., determining the sparse beamforming solution from the BSs to the users). The paper formulates the hybrid backhaul and access link design problem by minimizing the total networkpower consumption. The paper solves the problem using a two-stage heuristic algorithm. At one stage, the sparse beamforming solution is found using a weighted mixed 11/12 normminimization approach; the correlation matrix of the quantization noise of the wireline backhaul links is computed using the classical rate-distortion theory. At the second stage, thetransmit powers of the wireless backhaul links are found by solving a power minimization problem subject to quality-of-service constraints, based on the principle of conservation ofrate by utilizing the rates found in the first stage. Simulation results suggest that the performance of the proposed algorithm approaches the global optimum solution, especially athigh signal-to-interference-plus-noise ratio (SINR).

Keywords: array signal processing;cloud computing;matrix algebra;minimisation;mobile radio;next generation networks;quality of service;quantisation (signal);radio accessnetworks;BS;CRAN;SINR;base station;capacity-limited wireline backhaul link;central processor;classical rate-distortion theory;cloud-radio access networks;core networkarchitecture;correlation matrix;joint hybrid backhaul-access link design;next generation mobile radio systems;power minimization problem;quality-of-service constraints;quantizationnoise;signal-to-interference-plus-noise ratio;sparse beamforming solution;total network power consumption;two-stage heuristic algorithm;weighted mixed l1/l2 norm minimizationapproach;Array signal processing;Interference;Minimization;Optimization;Quantization (signal);Wireless communication;Wireless sensor networks
[102] M. E. Eltayeb and K. Elkhalil and A. A. Mas'ud and T. Y. Al-Naffouri "Relay Selection with Limited and Noisy Feedback",  in 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall), Sep 2015. [abstract] [.bib]

Abstract Relay selection is a simple technique that achieves spatial diversity in cooperative relay networks. Nonetheless, relay selection algorithms generally require error-freechannel state information (CSI) from all cooperating relays. Practically, CSI acquisition generates a great deal of feedback overhead that could result in significant transmissiondelays. In addition to this, the fed back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set ofcooperating relays based on inaccurate feedback information. In this paper, we propose a relay selection algorithm that tackles the above challenges. Instead of allocating each relay adedicated channel for feedback, all relays share a pool of feedback channels. Following that, each relay feeds back its identity only if its effective channel(source-relay-destination) exceeds a threshold. After deriving closed-form expressions for the feedback load and the achievable rate, we show that the proposed algorithm drasticallyreduces the feedback overhead and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback from all relays.

Keywords: cooperative communication;diversity reception;fading channels;relay networks (telecommunication);CSI acquisition;additive noise;cooperating relays;cooperative relaynetworks;error-free channel state information;feedback channel information;feedback channels;noisy feedback;relay selection algorithms;source-relay-destination;spatialdiversity;transmission delays;Additive noise;Data communication;Fading channels;Feeds;Relay networks (telecommunications);Signal to noise ratio
[101] K. Elkhalil and M. E. Eltayeb and H. Dahrouj and T. Y. Al-Naffouri "Distributed User Selection in Network MIMO Systems with Limited Feedback",  in 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall), Sep 2015. [abstract] [.bib]

Abstract We propose a distributed user selection strategy in a network MIMO setting with M base stations serving K users. Each base station is equipped with L antennas, where LM â‰ھ K.The conventional selection strategy is based on a well known technique called semi-orthogonal user selection when the zero-forcing beamforming (ZFBF) is adopted. Such technique,however, requires perfect channel state information at the transmitter (CSIT), which might not be available or need large feedback overhead. This paper proposes an alternativedistributed user selection technique where each user sets a timer that is inversely proportional to his channel quality indicator (CQI), as a means to reduce the feedback overhead. Theproposed strategy allows only the user with the highest CQI to respond with a feedback. Such technique, however, remains collision free only if the transmission time is shorter thanthe difference between the strongest user timer and the second strongest user timer. To overcome the situation of longer transmission times, the paper proposes another feedbackstrategy that is based on the theory of compressive sensing, where collision is allowed and all users encode their feedback information and send it back to the base-stationssimultaneously. The paper shows that the problem can be formulated as a block sparse recovery problem which is agnostic on the transmission time, which makes it a good alternative tothe timer approach when collision is dominant.

Keywords: MIMO communication;antennas;radio transmitters;antennas;base stations;channel quality indicator;channel state information;distributed user selection;network MIMOsystems;semi-orthogonal user selection;transmitter;zero-forcing beamforming;Antennas;Array signal processing;Channel state information;Complexity theory;Compressedsensing;Computers;MIMO
[100] H. A. J. Alshamary , T. Al-naffouri , A. Zaib and W. Xu "Optimal non-coherent data detection for massive SIMO wireless systems: A polynomial complexity solution",  in 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE), Aug 2015. [abstract] [.bib]


This paper considers the joint maximum likelihood (ML) channel estimation and data detection problem for massive SIMO (single input multiple output) wireless systems. Wepropose efficient algorithms achieving the exact ML non-coherent data detection, for both constant-modulus constellations and nonconstant-modulus constellations. Despite a large numberof unknown channel coefficients in massive SIMO systems, we show that the expected computational complexity is linear in the number of receive antennas and polynomial in channelcoherence time. To the best of our knowledge, our algorithms are the first efficient algorithms to achieve the exact joint ML channel estimation and data detection performance formassive SIMO systems with general constellations. Simulation results show our algorithms achieve considerable performance gains at a low computational complexity.

Keywords: channel estimation;maximum likelihood detection;maximum likelihood estimation;optimisation;radiocommunication;data detection problem;joint maximum likelihood channelestimation;massive SIMO wireless system;nonconstant modulus constellation;optimal noncoherent data detection;polynomial complexity solution;single input multiple output wirelesssystem;Channel estimation;Computational complexity;Decoding;MIMO;Maximum likelihood estimation;Receiving antennas;Signal processing algorithms;Massive SIMO systems;Maximumlikelihood;noncoherent channel estimation and data detection

M. T. Alkhodary and T. Ballal and T. Y. Al-Najfouri and A. H. Muqaibel

"Low-sampling-rate M-ary multiple access UWB communications in multipath channels",  in 2015 23rd European Signal Processing Conference (EUSIPCO), Aug 2015. [abstract] [.bib]


The desirable characteristics of ultra-wideband (UWB) technology are challenged by formidable sampling frequency, performance degradation in the presence of multi-user interference, and complexity of the receiver due to the channel estimation process. In this paper, a low-rate-sampling technique is used to implement M-ary multiple access UWB communications, in both the detection and channel estimation stages. A novel approach is used for multiple-access-interference (MAI) cancelation for the purpose of channel estimation. Results show reasonable performance of the proposed receiver for different number of users operating many times below Nyquist rate.

Keywords: channel estimation;interference suppression;multi-access systems;multipath channels;radio receivers;signal detection;signal sampling;ultra wideband communication;wireless channels;MAI cancelation;Nyquist rate;channel estimation process;low-sampling-rate M-ary multiple access UWB communication;multipath channel;multiple access interference cancelation;multiuser interference;receiver complexity;ultra wideband technology;Channel estimation;Correlation;Europe;Interference;Modulation;Receivers;Channel Estimation;Low Sampling;Multiple-access-interference cancelation;Ultra-Wideband
[98] A. Zaib and M. Masood and M. Ghogho and T. Y. Al-Naffouri "Distributive estimation of frequency selective channels for massive MIMO systems",  in 2015 23rd European Signal Processing Conference (EUSIPCO), Aug 2015. [abstract] [.bib]

Abstract We consider frequency selective channel estimation in the uplink of massive MIMO-OFDM systems, where our major concern is complexity. A low complexity distributed LMMSEalgorithm is proposed that attains near optimal channel impulse response (CIR) estimates from noisy observations at receive antenna array. In proposed method, every antenna estimatesthe CIRs of its neighborhood followed by recursive sharing of estimates with immediate neighbors. At each step, every antenna calculates the weighted average of shared estimates whichconverges to near optimal LMMSE solution. The simulation results validate the near optimal performance of proposed algorithm in terms of mean square error (MSE).

Keywords: MIMO communication;OFDM modulation;antenna arrays;channel estimation;mean square error methods;receiving antennas;recursive estimation;wireless channels;CIR;frequencyselective channels distributive estimation;low complexity distributed LMMSE algorithm;massive MIMO-OFDM system;mean square error;optimal channel impulse response;receive antennaarray;recursive sharing;Antenna arrays;Arrays;Channel estimation;Covariance matrices;Estimation;MIMO;Channel estimation;LMMSE;Least squares;distributed estimation;massive MIMO
[97] F. Sana and K. Katterbauer and T. Al-naffouri and I. Hoteit "Enhanced recovery of subsurface geological structures using compressed sensing and the Ensemble Kalman filter",  in 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2015. [abstract] [.bib]

Abstract Recovering information on subsurface geological features, such as flow channels, holds significant importance for optimizing the productivity of oil reservoirs. The flowchannels exhibit high permeability in contrast to low permeability rock formations in their surroundings, enabling formulation of a sparse field recovery problem. The Ensemble Kalmanfilter (EnKF) is a widely used technique for the estimation of subsurface parameters, such as permeability. However, the EnKF often fails to recover and preserve the channel structuresduring the estimation process. Compressed Sensing (CS) has shown to significantly improve the reconstruction quality when dealing with such problems. We propose a new scheme based onCS principles to enhance the reconstruction of subsurface geological features by transforming the EnKF estimation process to a sparse domain representing diverse geological structures.Numerical experiments suggest that the proposed scheme provides an efficient mechanism to incorporate and preserve structural information in the estimation process and results insignificant enhancement in the recovery of flow channel structures.

Keywords: Kalman filters;compressed sensing;geophysical signal processing;hydrocarbon reservoirs;numerical analysis;permeability;rocks;signal reconstruction;EnKF estimationprocess;compressed sensing;ensemble Kalman filter;flow channel structure recovery;information recovery;numerical experiment;oil reservoir;permeability rock formation;reconstructionquality;subsurface geological feature reconstruction;subsurface geological structure recovery;subsurface parameters estimation;Dictionaries;Estimation;Geology;Kalman filters;Matchingpursuit algorithms;Permeability;Reservoirs;Compressed Sensing;Ensemble Kalman Filter;K-SVD;Orthogonal Matching Pursuit;Subsurface Characterization
[96] A. Douik and H. Dahrouj and T. Y. Al-Naffouri and M. S. Alouini "Coordinated scheduling for the downlink of cloud radio-access networks",  in 2015 IEEE International Conference on Communications (ICC), Jun 2015. [abstract] [.bib]

Abstract This paper addresses the coordinated scheduling problem in cloud-enabled networks. Consider the downlink of a cloud-radio access network (CRAN), where the cloud is onlyresponsible for the scheduling policy and the synchronization of the transmit frames across the connected base-stations (BS). The transmitted frame of every BS consists of severaltime/frequency blocks, called power-zones (PZ), maintained at fixed transmit power. The paper considers the problem of scheduling users to PZs and BSs in a coordinated fashion acrossthe network, by maximizing a network-wide utility under the practical constraint that each user cannot be served by more than one base-station, but can be served by one or morepower-zones within each base-station frame. The paper solves the problem using a graph theoretical approach by introducing the scheduling graph in which each vertex represents anassociation of users, PZs and BSs. The problem is formulated as a maximum weight clique, in which the weight of each vertex is the benefit of the association represented by thatvertex. The paper further presents heuristic algorithms with low computational complexity. Simulation results show the performance of the proposed algorithms and suggest that theheuristics perform near optimal in low shadowing environments.

Keywords: graph theory;radio access networks;CRAN;base-station frame;cloud radio-access networks;coordinated scheduling problem;maximum weight clique;scheduling graph;Heuristicalgorithms;Interference;Optimal scheduling;Processor scheduling;Schedules;Scheduling;Shadow mapping;Coordinated scheduling;maximum weight clique problem;optimal and near optimalscheduling
[95] L. H. Afify and H. ElSawy and T. Y. Al-Naffouri and M. S. Alouini "Error performance analysis in K-tier uplink cellular networks using a stochastic geometric approach",  in 2015 IEEE International Conference on Communication Workshop (ICCW), Jun 2015. [abstract] [.bib]

Abstract In this work, we develop an analytical paradigm to analyze the average symbol error probability (ASEP) performance of uplink traffic in a multi-tier cellular network. Theanalysis is based on the recently developed Equivalent-in-Distribution approach that utilizes stochastic geometric tools to account for the network geometry in the performancecharacterization. Different from the other stochastic geometry models adopted in the literature, the developed analysis accounts for important communication system parameters and goesbeyond signal-to-interference-plus-noise ratio characterization. That is, the presented model accounts for the modulation scheme, constellation type, and signal recovery techniques tomodel the ASEP. To this end, we derive single integral expressions for the ASEP for different modulation schemes due to aggregate network interference. Finally, all theoreticalfindings of the paper are verified via Monte Carlo simulations.

Keywords: Monte Carlo methods;cellular radio;error analysis;error statistics;geometry;modulation;radiofrequency interference;stochastic processes;telecommunication traffic;ASEP;K-tieruplink cellular networks;Monte Carlo simulations;average symbol error probability performance analysis;communication system parameters;constellation type;equivalent-in-distributionapproach;modulation scheme;multitier cellular network;network geometry;network interference aggregation;performance characterization;signal recoverytechniques;signal-to-interference-plus-noise ratio characterization;stochastic geometric tools;uplink traffic;Aggregates;Geometry;Interference;Random variables;Signal to noiseratio;Stochastic processes;Uplink;Aggregate interference distribution;equivalent-indistribution;multi-tier uplink cellular networks;per user power control;stochastic geometry
[94] A. Ali and H. Elsawy and T. Y. Al-Naffouri and M. S. Alouini "Narrowband interference parameterization for sparse Bayesian recovery",  in 2015 IEEE International Conference on Communications (ICC), Jun 2015. [abstract] [.bib]

Abstract This paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBIcancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosensub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use toolsfrom stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recoverymethod for NBI mitigation.

Keywords: Bayes methods;compressed sensing;frequency division multiple access;frequency-domain analysis;radiofrequency interference;NBI cancellation scheme;SC-FDMA system;compressedsensing;frequency domain sparsity;narrowband interference parameterization;single carrier-frequency division multiple access system;sparse Bayesian recovery;stochastic geometry;unknownsignal;Bayes methods;Bit error rate;Frequency-domain analysis;Geometry;Interference;Narrowband;Receivers;Bayesian sparse recovery;Narrowband interference;SC-FDMA;compressedsensing;stochastic geometry
[93] S. Sorour and N. Aboutoraby and T. Y. Al-Naffouri and M. S. Alouini "A graph model for opportunistic network coding",  in 2015 International Symposium on Network Coding (NetCod), Jun 2015. [abstract] [.bib]

Abstract Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunisticnetwork coding (ONC) scenarios, with limited increase in complexity. In this paper, we design a simple IDNC-like graph model for a specific subclass of ONC, by introducing a moregeneralized definition of its vertices and the notion of vertex aggregation in order to represent the storage of non-instantly-decodable packets in ONC. Based on this representation,we determine the set of pairwise vertex adjacency conditions that can populate this graph with edges so as to guarantee decodability or aggregation for the vertices of each clique inthis graph. We then develop the algorithmic procedures that can be applied on the designed graph model to optimize any performance metric for this ONC subclass. A case study onreducing the completion time shows that the proposed framework improves on the performance of IDNC and gets very close to the optimal performance.

Keywords: graph theory;network coding;IDNC like graph model;IDNC trigger;ONC;decodable network coding;graph based analysis;graph model;opportunistic network coding;pairwise vertexadjacency;vertex aggregation;Algorithm design and analysis;Complexity theory;Decoding;Encoding;Measurement;Network coding;Receivers

A. Douik , S. Sorour , T. Y. Al-Naffouri , H. C. Yang and M. S. Alouini

"Delay reduction in multi-hop device-to-device communication using network coding",  in 2015 International Symposium on Network Coding (NetCod), Jun 2015. [abstract] [.bib]


This paper considers the problem of reducing the broadcast delay of wireless networks using instantly decodable network coding (IDNC) based device-to-device (D2D)communications. In D2D-enabled networks, devices help hasten the recovery of the lost packets of devices in their transmission range by sending network coded packets. To solve theproblem, the different events occurring at each device are identified so as to derive an expression for the probability distribution of the decoding delay. The joint optimizationproblem over the set of transmitting devices and the packet combinations of each is formulated. Due to the high complexity of finding the optimal solution, this paper focuses oncooperation without interference between the transmitting users. The optimal solution, in such interference-less scenario, is expressed using a graph theory approach by introducing thecooperation graph. Extensive simulations compare the decoding delay experienced in the Point to Multi-Point (PMP), the fully connected D2D (FC-D2D) and the more practical partiallyconnected D2D (PC-D2D) configurations and suggest that the PC-D2D outperforms the FC-D2D in all situations and provides an enormous gain for poorly connected networks.

Keywords: decoding;delays;graph theory;network coding;radio equipment;radio networks;D2D communications;D2D enabled networks;IDNC;PMP;broadcast delay;cooperation graph;decodingdelay;delay reduction;device-to-device communications;graph theory;instantly decodable network coding;multihop device-to-device communication;network coding;packet combinations;pointto multi-point;probability distribution;sending network coded packets;transmitting devices;transmitting users;wireless networks;Conferences;Decoding;Delays;Indexes;Networkcoding;Optimization;Wireless communication;Delay reduction;Device-todevice communications;Fully and Partially connected networks;Instantly decodable network coding
[91] A. Douik , H. Dahrouj , T. Y. Al-Naffouri and M. S. Alouini "Cost-effective backhaul design using hybrid radio/free-space optical technology",  in 2015 IEEE International Conference on Communication Workshop (ICCW), Jun 2015. [abstract] [.bib]


The deluge of date rate in today's networks poses a cost burden on the backhaul network design. Developing cost efficient backhaul solutions becomes an interesting, yetchallenging, problem. Traditional technologies for backhaul networks include either radio-frequency backhauls (RF) or optical fibres (OF). While RF is a cost-effective solution ascompared to OF, it supports lower data rate requirements. Another promising backhaul solution that may combine both a high data rate and a relatively low cost is the free-space optics(FSO). FSO, however, is sensitive to nature conditions (e.g., rain, fog, line-ofsight, etc.). A more reliable alternative is, therefore, to combine RF and FSO solutions through ahybrid structure called hybrid RF/FSO. Consider a backhaul network, where the base-stations (BS) can be connected to each other either via OF or hybrid RF/FSO backhaul links. The paperaddresses the problem of minimizing the cost of backhaul planning under connectivity and data rates constraints, so as to choose the appropriate costeffective backhaul type between BSs(i.e., either OF or hybrid RF/FSO). The paper solves the problem using graph theory techniques by introducing the corresponding planning graph. It shows that under a specifiedrealistic assumption about the cost of OF and hybrid RF/FSO links, the problem is equivalent to a maximum weight clique problem, which can be solved with moderate complexity.Simulation results show that our proposed solution shows a close-to-optimal performance, especially for practical prices of the hybrid RF/FSO.

Keywords: cellular radio;cost reduction;graph theory;optical fibre networks;telecommunication network planning;backhaul planning cost minimization;base-stations;cellularnetworks;cost-effective backhaul network design;data rate requirements;free-space optics;graph theory techniques;hybrid FSO backhaul links;hybrid RF backhaul links;hybrid free-spaceoptical technology;hybrid radio technology;maximum weight clique problem;optical fibres;radio-frequency backhauls;Approximation methods;Hybrid power systems;Next generationnetworking;Planning;Radio frequency;Reliability;Transceivers;Network planning;backhaul network design;cost minimization;free-space optic;optical fibre

A. Douik and S. Sorour and T.Y. Al-Naffouri and H.C. Yang and M.S. Alouini

"Delay Reduction with Interference-less Cooperation Between Users Using Network Coding",  in IEEE International Symposium on Network Coding (NetCod'15), Jun 2015. [.bib]
[89] A. Moubayed and S. Sorour and T. Al-naffouri and M. S. Alouini "Collaborative Multi-Layer Network Coding in Hybrid Cellular Cognitive Radio Networks",  in 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), May 2015. [abstract] [.bib]

Abstract In this paper, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay)cellular cognitive radio networks. This scheme allows the uncoordinated collaboration between the collocated primary and cognitive radio base-stations in order to minimize their own aswell as each other's packet recovery overheads, thus by improving their throughput. The proposed scheme ensures that each network's performance is not degraded by its help to the othernetwork. Moreover, it guarantees that the primary network's interference threshold is not violated in the same and adjacent cells. Yet, the scheme allows the reduction of the recoveryoverhead in the collocated primary and cognitive radio networks. The reduction in the cognitive radio network is further amplified due to the perfect detection of spectrum holes whichallows the cognitive radio base station to transmit at higher power without fear of violating the interference threshold of the primary network. For the secondary network, simulationresults show reductions of 20% and 34% in the packet recovery overhead, compared to the non-collaborative scheme, for low and high probabilities of primary packet arrivals,respectively. For the primary network, this reduction was found to be 12%.

Keywords: cellular radio;cognitive radio;network coding;radio spectrum management;cognitive radio base station;cognitive radio base-stations;collaborative packet recovery;collocatedprimary base-stations;hybrid cellular cognitive radio networks;interference threshold;packet recovery overheads;primary network;primary packet arrivals;prioritized multi-layer networkcoding scheme;secondary network;spectrum holes;Automatic repeat request;Base stations;Cognitive radio;Collaboration;Interference;Network coding;Simulation
[88] G. Kaddoum and M. F. A. Ahmed and T. Y. Al-Naffouri "Differential on-on keying: A robust non-coherent digital modulation scheme",  in 2015 International Conference on Information and Communication Technology Research (ICTRC), May 2015. [abstract] [.bib]

Abstract A robust digital modulation scheme, called differential on-on keying (DOOK), is presented in this paper which outperforms the conventional on-off keying (OOK). In thisscheme, a sinusoidal signal is transmitted during the first half of the bit duration while a replica or an inverted version of the sinusoidal signal is transmitted during the secondhalf for logic one or logic zero, respectively. Non-coherent receiver correlates the two halves of the received signal over half bit duration to construct a decision variable. Biterror performance is analyzed over AWGN and Rayleigh fading channels and compared to the conventional OOK.

Keywords: Rayleigh channels;amplitude shift keying;fading channels;signal processing;AWGN channels;DOOK;Rayleigh fading channels;bit duration;bit error performance;conventional on-offkeying;decision variable;differential on-on keying;half bit duration;logic one;logic zero;noncoherent receiver;received signal;robust digital modulation scheme;robust noncoherentdigital modulation scheme;sinusoidal signal;Bit error rate;Detectors;Fading;Receivers;Signal to noise ratio;Wireless sensor networks;DOOK;Performance analysis;Robust non-coherentmodulation;WSNs
[87] L. H. Afify and H. ElSawy and T. Y. Al-Naffouri and M. S. Alouini "Error performance analysis in downlink cellular networks with interference management",  in 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), May 2015. [abstract] [.bib]

Abstract Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models havesucceeded to account for the cellular network geometry, they mostly Abstract many important wireless communication system aspects (e.g., modulation techniques, signal recoverytechniques). Recently, a novel stochastic geometry model, based on the Equivalent-in-Distribution (EiD) approach, succeeded to capture the aforementioned communication system aspectsand extend the analysis to averaged error performance, however, on the expense of increasing the modeling complexity. Inspired by the EiD approach, the analysis developed in [1] takesinto consideration the key system parameters, while providing a simple tractable analysis. In this paper, we extend this framework to study the effect of different interferencemanagement techniques in downlink cellular network. The accuracy of the proposed analysis is verified via Monte Carlo simulations.

Keywords: Monte Carlo methods;cellular radio;radiofrequency interference;telecommunication network management;EiD;Equivalent-in-Distribution;Monte Carlo simulations;averaged errorperformance;cellular network geometry;downlink cellular networks;error performance analysis;interference management;interference management techniques;key system parameters;modulationtechniques;network interference;signal recovery techniques;stochastic geometry;stochastic geometry model;tractable analysis;wireless communication system;Aggregates;Analyticalmodels;Downlink;Error probability;Interference;Signal to noise ratio;Stochastic processes;Cellular networks;equivalent-in-distribution;interference management;stochasticgeometry;symbol error probability
[86] T. Ballal and T. Y. Al-Naffouri "Improved linear least squares estimation using bounded data uncertainty",  in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2015. [abstract] [.bib]

Abstract This paper addresses the problemof linear least squares (LS) estimation of a vector x from linearly related observations. In spite of being unbiased, the original LSestimator suffers from high mean squared error, especially at low signal-to-noise ratios. The mean squared error (MSE) of the LS estimator can be improved by introducing some form ofregularization based on certain constraints. We propose an improved LS (ILS) estimator that approximately minimizes the MSE, without imposing any constraints. To achieve this, we allowfor perturbation in the measurement matrix. Then we utilize a bounded data uncertainty (BDU) framework to derive a simple iterative procedure to estimate the regularization parameter.Numerical results demonstrate that the proposed BDU-ILS estimator is superior to the original LS estimator, and it converges to the best linear estimator, thelinear-minimum-mean-squared error estimator (LMMSE), when the elements of x are statistically white.

Keywords: iterative methods;matrix algebra;mean square error methods;signal processing;BDU-ILS estimator;LMMSE;bounded data uncertainty;bounded data uncertainty framework;improvedlinear least squares estimation;linear least squares estimation;linear-minimum-mean-squared error estimator;mean squared error;measurement matrix;simple iterativeprocedure;Estimation;Least squares approximations;Mathematical model;Optimized production technology;Signal to noise ratio;Uncertainty;bounded data uncertainty;least squares;linearestimation;mean squared error;regularization
[85] T. Bouchoucha and S. Ahmed and T. Y. Al-Naffouri and M. S. Alouini "Closed-form solution to directly design face waveforms for beampatterns using planar array",  in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2015. [abstract] [.bib]

Abstract In multiple-input multiple-output radar systems, it is usually desirable to steer transmitted power in the region-of-interest. To do this, conventional methods optimize thewaveform covariance matrix,R, for the desired beampattern, which is then used to generate actual transmitted waveforms. In this paper, we provide a low complexity closed-form solutionto design covariance matrix for the given planar beampattern using the planar array, which is then used to derive a novel closedform algorithm to directly design the finite-alphabetconstantenvelope waveforms. The proposed algorithm exploits the two-dimensional fast-Fourier-transform. The performance of our proposed algorithm is compared with the existing methodsthat are based on semi-definite quadratic programming with the advantage of a considerably reduced complexity.

Keywords: MIMO systems;acoustic signal processing;array signal processing;covariance matrices;fast Fourier transforms;radar;beampatterns;finite-alphabet constant-envelopewaveforms;multiple-input multiple-output radar systems;planar array;region-of-interest;semidefinite quadratic programming;two-dimensional fast-Fourier-transform;waveform covariancematrix;Arrays;Manganese;Multiple-input multiple-output radars;beampattern design;closed-form solution;two-dimensional fast-Fourier-transform;waveform design
[84] A. Ali, M. Masood, S. Al-Ghadhban and T. Y. Al-Naffouri "Bayesian narrowband interference mitigation in SC-FDMA",  in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2015. [abstract] [.bib]


This paper presents a novel narrowband interference (NBI) mitigation scheme for SC-FDMA systems. The proposed scheme exploits the frequency domain sparsity of the unknown NBIsignal and adopts a low complexity Bayesian sparse recovery procedure. In practice, however, the sparsity of the NBI is destroyed by a grid mismatch between NBI sources and SC-FDMAsystem. Towards this end, an accurate grid mismatch model is presented and a sparsifying transform is utilized to restore the sparsity of the unknown signal. Numerical results arepresented that depict the suitability of the proposed scheme for NBI mitigation.

Keywords: Bayes methods;frequency division multiple access;radiofrequency interference;Bayesian narrowband interference mitigation;SC-FDMA system;frequency domain sparsity;lowcomplexity Bayesian sparse recovery procedure;Bayes methods;Bit error rate;Estimation;Frequency-domain analysis;Interference;Narrowband;Transforms;Bayesian sparse recovery;LTE;NBImitigation;SC-FDMA;compressed sensing
[83] M. Masood and L. H. Afify and T. Y. Al-Naffouri "Efficient collaborative sparse channel estimation in massive MIMO",  in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2015. [abstract] [.bib]

Abstract We propose a method for estimation of sparse frequency selective channels within MIMO-OFDM systems. These channels are independently sparse and share a common support. Themethod estimates the impulse response for each channel observed by the antennas at the receiver. Estimation is performed in a coordinated manner by sharing minimal information amongneighboring antennas to achieve results better than many contemporary methods. Simulations demonstrate the superior performance of the proposed method.

Keywords: MIMO communication;OFDM modulation;channel estimation;estimation theory;transient response;MIMO-OFDM systems;collaborative sparse channel estimation;impulse response;massiveMIMO;minimal information;sparse frequency selective channels;Antenna arrays;Channel estimation;MIMO;OFDM;Receiving antennas;Reliability;OFDM;massive MIMO;sparse channel
[82] S. A. W. Shah and K. Abed-Meraim and T. Y. Al-Naffouri "Multi-Modulus algorithms using hyperbolic and givens rotations for blind deconvolution of mimo systems",  in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2015. [abstract] [.bib]

Abstract The issue of blind Multiple-Input and Multiple-Output (MIMO) deconvolution of communication system is addressed. Two new iterative Blind Source Separation (BSS) algorithmsare presented, based on the minimization of Multi-Modulus (MM) criterion. A pre-whitening filter is utilized to transform the problem into finding a unitary beamformer matrix. Then,applying iterative Givens and Hyperbolic rotations results in Givens Multi-modulus Algorithm (G-MMA) and Hyperbolic G-MMA (HG-MMA), respectively. Proposed algorithms are compared withseveral BSS algorithms in terms of Signal to Interference and Noise Ratio (SINR) and Symbol Error Rate (SER) and it was shown to outperform them.

Keywords: MIMO communication;array signal processing;blind source separation;deconvolution;error statistics;filtering theory;hyperbolic equations;iterative methods;minimisation;Givensmultimodulus algorithm;HG-MMA;MIMO system;SER;SINR;blind deconvolution;hyberbolic rotation;hyperbolic G-MMA;iterative BSS algorithm;iterative Givens rotations;iterative blind sourceseparation;multimodulus criterion minimization;multiple input multiple output;prewhitening filter;signal to interference and noise ratio;symbol error rate;unitary beamformermatrix;Deconvolution;Jacobian matrices;Signal to noise ratio;Givens and Hyperbolic rotations;blind source separation;constant modulus algorithm;multi-modulus algorithm
[81] H. Dahrouj , T. Y. Al-Naffouri and M. S. Alouini "Distributed cloud association in downlink multicloud radio access networks",  in 2015 49th Annual Conference on Information Sciences and Systems (CISS), Mar 2015. [abstract] [.bib]


This paper considers a multicloud radio access network (M-CRAN), wherein each cloud serves a cluster of base-stations (BS's) which are connected to the clouds through highcapacity digital links. The network comprises several remote users, where each user can be connected to one (and only one) cloud. This paper studies the user-to-cloud-assignmentproblem by maximizing a network-wide utility subject to practical cloud connectivity constraints. The paper solves the problem by using an auction-based iterative algorithm, which canbe implemented in a distributed fashion through a reasonable exchange of information between the clouds. The paper further proposes a centralized heuristic algorithm, with lowcomputational complexity. Simulations results show that the proposed algorithms provide appreciable performance improvements as compared to the conventional cloud-less assignmentsolutions.

Keywords: iterative methods;optimisation;radio access networks;auction-based iterative algorithm;centralized heuristic algorithm;cloud connectivity constraint;cloudless assignmentsolutions;distributed cloud association;downlink M-CRAN;low computational complexity;multicloud radio access network;network-wide utility;user-to-cloud-assignmentproblem;Antennas;Computational complexity;Downlink;Heuristic algorithms;Iterative methods;Optimization;Radio access networks
[80] A. Douik and S. Sorour and H. Tembine and M. S. Alouini and T. Y. Al-Naffouri "A game theoretic approach to minimize the completion time of network coded cooperative data exchange",  in 2014 IEEE Global Communications Conference, Dec 2014. [abstract] [.bib]

Abstract In this paper, we introduce a game theoretic framework for studying the problem of minimizing the completion time of instantly decodable network coding (IDNC) for cooperativedata exchange (CDE) in decentralized wireless network. In this configuration, clients cooperate with each other to recover the erased packets without a central controller. Game theoryis employed herein as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. We model the session byself-interested players in a non-cooperative potential game. The utility function is designed such that increasing individual payoff results in a collective behavior achieving both adesirable system performance in a shared network environment and the Pareto optimal solution. We further show that our distributed solution achieves the centralized solution. Throughextensive simulations, our approach is compared to the best performance that could be found in the conventional point-to-multipoint (PMP) recovery process. Numerical results show thatour formulation largely outperforms the conventional PMP scheme in most practical situations and achieves a lower delay.

Keywords: cooperative communication;decoding;electronic data interchange;game theory;network coding;radio networks;telecommunication computing;CDE;IDNC;PMP scheme;Pareto optimalsolution;completion time minimization;cooperative data exchange;decentralized wireless network;distributed solution;game theoretic approach;instantly decodable networkcoding;noncooperative potential game;point-to-multipoint recovery process;self-interested players;shared network environment;utility function;Basestations;Decoding;Delays;Games;History;Network coding;Vectors;Cooperative data exchange;Nash equilibrium;instantly decodable network coding;non-cooperative games;potential game
[79] K. Elkhalil and M. E. Eltayeb and H. Shibli and H. R. Bahrami and T. Y. Al-Naffouri "Opportunistic relay selection in multicast relay networks using compressive sensing",  in 2014 IEEE Global Communications Conference, Dec 2014. [abstract] [.bib]

Abstract Relay selection is a simple technique that achieves spatial diversity in cooperative relay networks. However, for relay selection algorithms to make a selection decision,channel state information (CSI) from all cooperating relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates agreat deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed back channel information is usually corrupted by additive noise. Thiscould lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. In this paper, we introduce a limited feedbackrelay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the "strong" relays withlimited feedback. Following that, the CSI of the selected relays is estimated using linear minimum mean square error estimation. To minimize the effect of noise on the fed back CSI, weintroduce a back-off strategy that optimally backs-off on the noisy estimated CSI. For a fixed group size, we provide closed form expressions for the scaling law of the maximumequivalent SNR for both Decode and Forward (DF) and Amplify and Forward (AF) cases. Numerical results show that the proposed algorithm drastically reduces the feedback air-time andachieves a rate close to that obtained by selection algorithms with dedicated error-free feedback channels.

Keywords: amplify and forward communication;channel estimation;compressed sensing;cooperative communication;decode and forward communication;diversity reception;interferencesuppression;least mean squares methods;multicast communication;relay networks (telecommunication);wireless channels;AF case;CSI acquisition;CSI noisy estimation;DF case;additivenoise;amplify and forward communication;back-off strategy;channel state information;compressive sensing;cooperative relay network feedback overhead;decode and forwardcommunication;error-free feedback channel;fed back channel information;feedback air-time reduction;limited feedback relay selection algorithm;linear minimum mean square errorestimation;maximum equivalent SNR;multicast relay network transmission outage;opportunistic relay selection;spatial diversity;Noise measurement;Relays;Signal processingalgorithms;Signal to noise ratio;Throughput;Vectors;Amplify and Forward;Compressive Sensing;Decode and Forward;Feedback;Multicast;Relay selection
[78] A. Douik and S. Sorour and M. S. Alouini and T. Y. Al-Naffouri "Completion time reduction in instantly decodable network coding through decoding delay control",  in 2014 IEEE Global Communications Conference, Dec 2014. [abstract] [.bib]

Abstract For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completelyact against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling theother. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive thedecoding-delay-dependent expressions of the users' and their overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we use aheuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control oftheir decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic forcompletion time reduction. The gap in performance becomes significant for harsh erasure scenarios.

Keywords: network coding;optimisation;IDNC metrics;NP-hard problem;completion time reduction;decoding delay control;decoding-delay-dependent completion time expressions;instantlydecodable network coding;layered control;mean completion time;mean decoding delay;Algorithm design and analysis;Decoding;Delays;Network coding;Schedules;Wireless communication;Decodingdelay;Instantly decodable network coding;Minimum completion time
[77] H. Ali and S. Ahmed and T. Y. Al-Naffouri and S. Alouini "Reduction of snapshots for MIMO radar detection by block/group orthogonal matching pursuit",  in 2014 International Radar Conference, Oct 2014. [abstract] [.bib]

Abstract Multiple-input multiple-output (MIMO) radar works on the principle of transmission of independent waveforms at each element of its antenna array and is widely used forsurveillance purposes. In this work, we investigate MIMO radar target localization problem with compressive sensing. Specifically, we try to solve the problem of estimation of targetlocation in MIMO radar by group and block sparsity algorithms. It will lead us to a reduced number of snapshots required and also we can achieve better radar resolution. We will usegroup orthogonal matching pursuit (GOMP) and block orthogonal matching pursuit (BOMP) for our problem.

Keywords: MIMO radar;antenna arrays;radar antennas;BOMP;GOMP;MIMO radar detection;MIMO radar target localization problem;antenna array;block orthogonal matching pursuit;block sparsityalgorithms;block-group orthogonal matching pursuit;compressive sensing;group orthogonal matching pursuit;independent waveforms;multiple-input multiple-output radar;radarresolution;snapshot reduction;Arrays;Estimation;MIMO radar;Matching pursuit algorithms;Signal processing algorithms;Vectors;block orthogonal matching pursuit;compressive sensing;grouporthogonal matching pursuit
[76] A. Douik and S. Sorour and M. S. Alouini and T. Y. Al-Naffouri "On Minimizing the Maximum Broadcast Decoding Delay for Instantly Decodable Network Coding",  in 2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall), Sep 2014. [abstract] [.bib]

Abstract In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding(IDNC). Unlike the sum decoding delay, the maximum decoding delay as a definition of delay for IDNC allows a more equitable distribution of the delays between the different receiversand thus a better Quality of Service (QoS). In order to solve this problem, we first derive the expressions for the probability distributions of maximum decoding delay increments.Given these expressions, we formulate the problem as a maximum weight clique problem in the IDNC graph. Although this problem is known to be NP-hard, we design a greedy algorithm toperform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize thesum decoding delay and our policy to reduce the max decoding delay. Simulations results show that our policy gives a good agreement among all the delay aspects in all situations andoutperforms the sum decoding delay policy to effectively minimize the sum decoding delay when the channel conditions become harsher. They also show that our definition of delaysignificantly improve the number of served receivers when they are subject to strict delay constraints.

Keywords: decoding;greedy algorithms;network coding;optimisation;quality of service;IDNC;QoS;effective packet selection;equitable distribution;generalized instantly decodable networkcoding;greedy algorithm;max decoding delay;maximum broadcast decoding delay;quality of service;sum decoding delay;Conferences;Decoding;Delays;Greedy algorithms;Networkcoding;Receivers;Simulation
[75] M. Masood and T. Y. Al-Naffouri "Support agnostic Bayesian recovery of jointly sparse signals",  in 2014 22nd European Signal Processing Conference (EUSIPCO), Sep 2014. [abstract] [.bib]

Abstract A matching pursuit method using a Bayesian approach is introduced for recovering a set of sparse signals with common support from a set of their measurements. This methodperforms Bayesian estimates of joint-sparse signals even when the distribution of active elements is not known. It utilizes only the a priori statistics of noise and the sparsity rateof the signal, which are estimated without user intervention. The method utilizes a greedy approach to determine the approximate MMSE estimate of the joint-sparse signals. Simulationresults demonstrate the superiority of the proposed estimator.

Keywords: Bayes methods;iterative methods;least mean squares methods;signal processing;time-frequency analysis;Bayesian estimates;MMSE estimate;active elements;greedy approach;jointsparse signals;matching pursuit;support agnostic Bayesian recovery;Bayes methods;Greedy algorithms;Matching pursuit algorithms;Signal to noise ratio;Sparse matrices;Vectors
[74] T. Ballal and T. Y. Al-Naffouri "Low-sampling-rate ultra-wideband digital receiver using equivalent-time sampling",  in 2014 IEEE International Conference on Ultra-WideBand (ICUWB), Sep 2014. [abstract] [.bib]

Abstract In this paper, we propose an all-digital scheme for ultra-wideband symbol detection. In the proposed scheme, the received symbols are sampled many times below the Nyquistrate. It is shown that when the number of symbol repetitions, P, is co-prime with the symbol duration given in Nyquist samples, the receiver can sample the received data P times belowthe Nyquist rate, without loss of fidelity. The proposed scheme is applied to perform channel estimation and binary pulse position modulation (BPPM) detection. Results are presentedfor two receivers operating at two different sampling rates that are 10 and 20 times below the Nyquist rate. The feasibility of the proposed scheme is demonstrated in differentscenarios, with reasonable bit error rates obtained in most of the cases.

Keywords: pulse position modulation;radio receivers;signal detection;signal sampling;ultra wideband communication;BPPM detection;Nyquist rate;Nyquist samples;all-digital scheme;binarypulse position modulation detection;bit error rates;channel estimation;equivalent-time sampling;low-sampling-rate ultra-wideband digital receiver;ultra-wideband symboldetection;Approximation methods;Bit error rate;Channel estimation;Conferences;Modulation;Receivers;Ultra wideband technology;PPM;UWB communications;detection;pulse positionmodulation;sub-sampling
[73] T. Ballal and T. Y. Al-Naffouri "Low-sampling-rate ultra-wideband channel estimation using a bounded-data-uncertainty approach",  in 2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Jun 2014. [abstract] [.bib]

Abstract This paper proposes a low-sampling-rate scheme for ultra-wideband channel estimation. In the proposed scheme, P pulses are transmitted to produce P observations. Theseobservations are exploited to produce channel impulse response estimates at a desired sampling rate, while the ADC operates at a rate that is P times less. To avoid loss of fidelity,the interpulse interval, given in units of sampling periods of the desired rate, is restricted to be co-prime with P. This condition is affected when clock drift is present and thetransmitted pulse locations change. To handle this situation and to achieve good performance without using prior information, we derive an improved estimator based on the bounded datauncertainty (BDU) model. This estimator is shown to be related to the Bayesian linear minimum mean squared error (LMMSE) estimator. The performance of the proposed sub-sampling schemewas tested in conjunction with the new estimator. It is shown that high reduction in sampling rate can be achieved. The proposed estimator outperforms the least squares estimator inmost cases; while in the high SNR regime, it also outperforms the LMMSE estimator.

Keywords: belief networks;channel estimation;least mean squares methods;ultra wideband communication;Bayesian linear minimum mean squared error estimator;LMMSE estimator;bounded datauncertainty model;bounded-data-uncertainty approach;channel impulse response estimates;interpulse interval;low-sampling-rate ultra-wideband channel estimation;sub-samplingscheme;Channel estimation;Clocks;Signal to noise ratio;Ultra wideband technology;Uncertainty;Wireless communication
[72] A. Ali and A. Al-Zahrani and T. Y. Al-Naffouri and A. Naguib "Receiver based PAPR reduction in OFDMA",  in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2014. [abstract] [.bib]

Abstract High peak-to-average power ratio is one of the major drawbacks of orthogonal frequency division multiplexing (OFDM). Clipping is the simplest peak reduction scheme, however,it requires clipping mitigation at the receiver. Recently compressed sensing has been used for clipping mitigation (by exploiting the sparse nature of clipping signal). However,clipping estimation in multi-user scenario (i.e., OFDMA) is not straightforward as clipping distortions overlap in frequency domain and one cannot distinguish between distortions fromdifferent users. In this work, a collaborative clipping removal strategy is proposed based on joint estimation of the clipping distortions from all users. Further, an effective dataaided channel estimation strategy for clipped OFDM is also outlined. Simulation results are presented to justify the effectiveness of the proposed schemes.

Keywords: OFDM modulation;channel estimation;compressed sensing;frequency division multiple access;radio receivers;OFDMA;clipping estimation;clipping mitigation;collaborative clippingremoval strategy;compressed sensing;data aided channel estimation strategy;multi-user scenario;orthogonal frequency division multiplexing;peak-to-average power ratio;receiver;Channelestimation;Estimation;Peak to average power ratio;Reliability;Time-domain analysis;Vectors;OFDMA;PAPR reduction;channel estimation;clipping;compressed sensing
[71] M. E. Eltayeb and T. Y. Al-Naffouri and H. R. Bahrami "Downlink scheduling using non-orthogonal uplink beams",  in 2014 IEEE Wireless Communications and Networking Conference (WCNC), Apr 2014. [abstract] [.bib]

Abstract Opportunistic schedulers rely on the feedback of the channel state information of users in order to perform user selection and downlink scheduling. This feedback increaseswith the number of users, and can lead to inefficient use of network resources and scheduling delays. We tackle the problem of feedback design, and propose a novel class ofnonorthogonal codes to feed back channel state information. Users with favorable channel conditions simultaneously transmit their channel state information via non-orthogonal beams tothe base station. The proposed formulation allows the base station to identify the strong users via a simple correlation process. After deriving the minimum required code length andclosed-form expressions for the feedback load and downlink capacity, we show that: the proposed algorithm reduces the feedback load while matching the achievable rate of full feedbackalgorithms operating over a noiseless feedback channel; and the proposed codes are superior to the Gaussian codes.

Keywords: codes;feedback;radiocommunication;channel state information;closed form expressions;correlation process;downlink capacity;downlink scheduling;feedback design;feedback loadwhile matching;minimum required code length;nonorthogonal code;nonorthogonal uplink beams;Correlation;Downlink;Interference;Signal to noise ratio;Uplink;Vectors
[70] K. Majeed and S. Sorour and T. Y. Al-Naffouri and S. Valaee "Indoor localization using unsupervised manifold alignment with geometry perturbation",  in 2014 IEEE Wireless Communications and Networking Conference (WCNC), Apr 2014. [abstract] [.bib]

Abstract The main limitation of deploying/updating Received Signal Strength (RSS) based indoor localization is the construction of fingerprinted radio map, which is quite a hectic andtime-consuming process especially when the indoor area is enormous and/or dynamic. Different approaches have been undertaken to reduce such deployment/update efforts, but theperformance degrades when the fingerprinting load is reduced below a certain level. In this paper, we propose an indoor localization scheme that requires as low as 1% fingerprintingload. This scheme employs unsupervised manifold alignment that takes crowd sourced RSS readings and localization requests as source data set and the environment's plan coordinates asdestination data set. The 1% fingerprinting load is only used to perturb the local geometries in the destination data set. Our proposed algorithm was shown to achieve less than 5 mmean localization error with 1% fingerprinting load and a limited number of crowd sourced readings, when other learning based localization schemes pass the 10 m mean error with thesame information.

Keywords: geometry;indoor radio;perturbation techniques;radio direction-finding;telecommunication computing;unsupervised learning;RSS based indoor localization;crowd sourced RSSreadings;deployment-update efforts;destination data set;environment plan coordinates;fingerprinted radio map;fingerprinting load;indoor area;learning based localization schemes;localgeometries;localization requests;received signal strength based indoor localization;source data set;unsupervised manifold alignment;Calibration;Geometry;Indoorenvironments;Manifolds;Mobile computing;Vectors;Zirconium
[69] A. Douik and S. Sorour and M. S. Alouini and T. Y. Al-Naffouri "Delay reduction in lossy intermittent feedback for generalized instantly decodable network coding",  in 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Oct 2013. [abstract] [.bib]

Abstract In this paper, we study the effect of lossy intermittent feedback loss events on the multicast decoding delay performance of generalized instantly decodable network coding.These feedback loss events create uncertainty at the sender about the reception statues of different receivers and thus uncertainty to accurately determine subsequent instantlydecodable coded packets. To solve this problem, we first identify the different possibilities of uncertain packets at the sender and their probabilities. We then derive the expressionof the mean decoding delay. We formulate the Generalized Instantly Decodable Network Coding (G-IDNC) minimum decoding delay problem as a maximum weight clique problem. Since findingthe optimal solution is NP-hard, we design a variant of the algorithm employed in [1]. Our algorithm is compared to the two blind graph update proposed in [2] through extensivesimulations. Results show that our algorithm outperforms the blind approaches in all the situations and achieves a tolerable degradation, against the perfect feedback, for largefeedback loss period.

Keywords: computational complexity;decoding;network coding;G-IDNC minimum decoding delay problem;NP-hard optimal solution;blind graph update;decodable coded packets;delayreduction;generalized instantly-decodable network coding;lossy intermittent feedback loss events;maximum weight clique problem;mean decoding delay;multicast decoding delayperformance;receiver reception statue;uncertain packets;Lossy Intermittent Feedback;Maximum Weight Clique Problem;Minimum Decoding Delay;Multicast Channels
[68] A. Al-Rabah , M. Masood , A. Ali and T. Y. Al-Naffouri "Receiver-based Bayesian PAPR reduction in OFDM",  in 21st European Signal Processing Conference (EUSIPCO 2013), Sep 2013. [abstract] [.bib]


One of the main drawbacks of OFDM systems is the high peak-to-average-power ratio (PAPR). Most of the PAPR reduction techniques require transmitter-based processing. However,we propose a receiver-based low-complexity clipping signal recovery method. This method is able to i) reduce PAPR via a simple clipping scheme, ii) use a Bayesian recovery algorithm toreconstruct the distortion signal with high accuracy, and iii) is energy efficient due to low complexity. The proposed method is robust against variation in noise and signalstatistics. The method is enhanced by making use of all prior information such as, the locations and the phase of the non-zero elements of the clipping signal. Simulation resultsdemonstrate the superiority of using the proposed algorithm over other recovery algorithms.

Keywords: OFDM modulation;belief networks;receivers;signal reconstruction;Bayesian recovery algorithm;OFDM systems;high peak-to-average-power ratio;receiver-based Bayesian PAPRreduction technique;receiver-based low-complexity clipping signal recovery method;signal reconstruction;transmitter-based processing;Bayes methods;Bit error rate;Equations;Peak toaverage power ratio;Robustness;Vectors;OFDM;PAPR reduction;SABMP;Sparse signal estimation;tone reservation
[67] T. Y. Al-Naffouri and M. Moinuddin "Exact tracking analysis of the NLMS algorithm for correlated Gaussian inputs",  in 21st European Signal Processing Conference (EUSIPCO 2013), Sep 2013. [abstract] [.bib]

Abstract This work presents an exact tracking analysis of the Normalized Least Mean Square (NLMS) algorithm for circular complex correlated Gaussian inputs. Unlike the existing works,the analysis presented neither uses separation principle nor small step-size assumption. The approach is based on the derivation of a closed form expression for the cumulativedistribution function (CDF) of random variables of the form (∥u∥D12)(∥u∥D22)-1 where u is a white Gaussian vector and D1 and D2 are diagonal matrices and using that to derive the firstand second moments of such variables. These moments are then used to evaluate the tracking behavior of the NLMS algorithm in closed form. Thus, both the steady-state mean-square-error(MSE) and mean-square-deviation (MSD )tracking behaviors of the NLMS algorithm are evaluated. The analysis is also used to derive the optimum step-size that minimizes the excess MSE(EMSE). Simulations presented for the steady-state tracking behavior support the theoretical findings for a wide range of step-size and input correlation.

Keywords: Gaussian distribution;adaptive filters;least mean squares methods;matrix algebra;random processes;vectors;CDF;EMSE;MSD;NLMS algorithm;adaptive filters;correlated Gaussianinputs;cumulative distribution function;diagonal matrices;exact tracking analysis;excess MSE;mean-square-deviation;normalized least mean square algorithm;random variables;steady-statemean-square-error;white Gaussian vector;Algorithm design and analysis;Analytical models;Correlation;Mathematical model;Random variables;Steady-state;Vectors;Adaptive filters;NLMSalgorithm;Tracking analysis
[66] A. A. Quadeer and M. S. Sohail and T. Y. Al-Naffouri "A compressed sensing based method with support refinement for impulse noise cancelation in DSL",  in 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Jun 2013. [abstract] [.bib]

Abstract This paper presents a compressed sensing based method to suppress impulse noise in digital subscriber line (DSL). The proposed algorithm exploits the sparse nature of theimpulse noise and utilizes the null carriers, already available in all practical DSL systems, for its estimation and cancelation. Specifically, compressed sensing is used for a coarseestimate of the impulse position, an a priori information based maximum aposteriori probability (MAP) metric for its refinement, followed by least squares (LS) or minimum mean squareerror (MMSE) estimation for estimating the impulse amplitudes. Simulation results show that the proposed scheme achieves higher rate as compared to other known sparse estimationalgorithms in literature. The paper also demonstrates the superior performance of the proposed scheme compared to the ITU-T G992.3 standard that utilizes RS-coding for impulse noiserefinement in DSL signals.

Keywords: Reed-Solomon codes;compressed sensing;digital subscriber lines;impulse noise;least mean squares methods;maximum likelihood estimation;DSL;ITU-T G992.3 standard;MAPmetric;RS-coding;compressed sensing based method;digital subscriber line;impulse noise refinement;impulse noise suppression;impulse position;least square error estimation;minimum meansquare error estimation;null carriers utilization;priori information based maximum a-posteriori probability;sparse estimation algorithm;Compressedsensing;DSL;Estimation;Noise;OFDM;Signal processing algorithms;Standards;DSL;Impulse noise;compressed sensing;estimation;sparse signal reconstruction
[65] H. J. Shibli and M. E. Eltayeb and T. Y. Al-Naffouri "A Bayesian matching pursuit based scheduling algorithm for feedback reduction in MIMO broadcast channels",  in 2013 Third International Conference on Communications and Information Technology (ICCIT), Jun 2013. [abstract] [.bib]

Abstract Opportunistic schedulers rely on the feedback of all users in order to schedule a set of users with favorable channel conditions. While the downlink channels can be easilyestimated at all user terminals via a single broadcast, several key challenges are faced during uplink transmission. First of all, the statistics of the noisy and fading feedbackchannels are unknown at the base station (BS) and channel training is usually required from all users. Secondly, the amount of network resources (air-time) required for feedbacktransmission grows linearly with the number of users. In this paper, we tackle the above challenges and propose a Bayesian based scheduling algorithm that 1) reduces the air-timerequired to identify the strong users, and 2) is agnostic to the statistics of the feedback channels and utilizes the a priori statistics of the additive noise to identify the strongusers. Numerical results show that the proposed algorithm reduces the feedback air-time while improving detection in the presence of fading and noisy channels when compared to recentcompressed sensing based algorithms. Furthermore, the proposed algorithm achieves a sum-rate throughput close to that obtained by noiseless dedicated feedback systems.

Keywords: Bayes methods;MIMO communication;broadcast channels;iterative methods;scheduling;Bayesian based scheduling algorithm;Bayesian matching pursuit based scheduling algorithm;MIMObroadcast channels;additive noise;base station;channel training;downlink channels;fading feedback channels;feedback reduction;feedback transmission;opportunistic schedulers;uplinktransmission;Compressed sensing;Downlink;Signal processing algorithms;Signal to noise ratio;Throughput;Vectors;Wireless communication
[64] M. F. A. Ahmed and T. Y. Al-Naffouri and M. S. Alouini "On the effect of correlated measurements on the performance of distributed estimation",  in 2013 IEEE International Conference on Communications (ICC), Jun 2013. [abstract] [.bib]

Abstract We address the distributed estimation of an unknown scalar parameter in Wireless Sensor Networks (WSNs). Sensor nodes transmit their noisy observations over multiple accesschannel to a Fusion Center (FC) that reconstructs the source parameter. The received signal is corrupted by noise and channel fading, so that the FC objective is to minimize theMean-Square Error (MSE) of the estimate. In this paper, we assume sensor node observations to be correlated with the source signal and correlated with each other as well. Thecorrelation coefficient between two observations is exponentially decaying with the distance separation. The effect of the distance-based correlation on the estimation quality isdemonstrated and compared with the case of unity correlated observations. Moreover, a closed-form expression for the outage probability is derived and its dependency on the correlationcoefficients is investigated. Numerical simulations are provided to verify our analytic results.

Keywords: fading channels;mean square error methods;probability;sensor fusion;wireless sensor networks;FC;MSE;WSN;channel fading;closed-form expression;correlationcoefficient;distributed estimation;fusion center;mean-square error;multiple access channel;outage probability;sensor node;wireless sensor networks;Correlation;Eigenvalues andeigenfunctions;Estimation;Fading;Noise;Resource management;Wireless sensor networks
[63] S. Sorour and T. Y. Al-Naffouri and M. S. Alouini "Collaborative multi-layer network coding for cellular cognitive radio networks",  in 2013 IEEE International Conference on Communications (ICC), Jun 2013. [abstract] [.bib]

Abstract In this paper, we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in underlay cellular cognitive radio networks. This scheme allowsthe collocated primary and cognitive radio base-stations to collaborate with each other, in order to minimize their own and each other's packet recovery overheads, and thus improvetheir throughput, without any coordination between them. This non-coordinated collaboration is done using a novel multi-layer instantly decodable network coding scheme, whichguarantees that each network's help to the other network does not result in any degradation in its own performance. It also does not cause any violation to the primary networksinterference thresholds in the same and adjacent cells. Yet, our proposed scheme both guarantees the reduction of the recovery overhead in collocated primary and cognitive radionetworks, and allows early recovery of their packets compared to non-collaborative schemes. Simulation results show that a recovery overhead reduction of 15% and 40% can be achieved byour proposed scheme in the primary and cognitive radio networks, respectively, compared to the corresponding non-collaborative scheme.

Keywords: cellular radio;cognitive radio;network coding;cognitive radio base-stations;collaborative multilayer network coding scheme;collaborative packet recovery;collocated primarybase station;novel multilayer instant decodable network coding scheme;primary networks interference thresholds;underlay cellular cognitive radio networks;Cognitiveradio;Collaboration;Delays;Interference;Network coding;Receivers
[62] S. Sorour and N. Aboutorab and P. Sadeghi and M. S. Karim and T. Y. Al-Naffouri and M. S. Alouini "Delay Reduction in Persistent Erasure Channels for Generalized Instantly Decodable Network Coding",  in 2013 IEEE 77th Vehicular Technology Conference (VTC Spring), Jun 2013. [abstract] [.bib]

Abstract In this paper, we consider the problem of minimizing the decoding delay of generalized instantly decodable network coding (G-IDNC) in persistent erasure channels (PECs). Bypersistent erasure channels, we mean erasure channels with memory, which are modeled as a Gilbert-Elliott two-state Markov model with good and bad channel states. In this scenario, thechannel erasure dependence, represented by the transition probabilities of this channel model, is an important factor that could be exploited to reduce the decoding delay. We firstformulate the G-IDNC minimum decoding delay problem in PECs as a maximum weight clique problem over the G-IDNC graph. Since finding the optimal solution of this formulation is NP-hard,we propose two heuristic algorithms to solve it and compare them using extensive simulations. Simulation results show that each of these heuristics outperforms the other in certainranges of channel memory levels. They also show that the proposed heuristics significantly outperform both the optimal strict IDNC in the literature and the channel-unaware G-IDNCalgorithms.

Keywords: Markov processes;decoding;network coding;G-IDNC graph;Gilbert-Elliott two-state Markov model;NP-hard;PEC;channel erasure dependence;channel memory levels;channel-unawaregeneralized instantly decodable network coding algorithms;decoding delay reduction;heuristic algorithms;maximum weight clique problem;persistent erasure channels;transitionprobabilities;Algorithm design and analysis;Decoding;Delays;Educational institutions;Heuristic algorithms;Network coding;Receivers
[61] T. Y. Al-Naffouri and M. Masood "Distribution agnostic structured sparsity recovery algorithms",  in 2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA), May 2013. [abstract] [.bib]

Abstract We present an algorithm and its variants for sparse signal recovery from a small number of its measurements in a distribution agnostic manner. The proposed algorithm findsBayesian estimate of a sparse signal to be recovered and at the same time is indifferent to the actual distribution of its non-zero elements. Termed Support Agnostic Bayesian MatchingPursuit (SABMP), the algorithm also has the capability of refining the estimates of signal and required parameters in the absence of the exact parameter values. The inherent feature ofthe algorithm of being agnostic to the distribution of the data grants it the flexibility to adapt itself to several related problems. Specifically, we present two important extensionsto this algorithm. One extension handles the problem of recovering sparse signals having block structures while the other handles multiple measurement vectors to jointly estimate therelated unknown signals. We conduct extensive experiments to show that SABMP and its variants have superior performance to most of the state-of-the-art algorithms and that too atlow-computational expense.

Keywords: iterative methods;signal processing;time-frequency analysis;Bayesian estimate;SABMP;block structures;distribution agnostic structured sparsity recovery algorithm;measurementvector;nonzero element;sparse signal recovery;support agnostic Bayesian matching pursuit;Bayes methods;Greedy algorithms;Matching pursuit algorithms;Sensors;Signal processingalgorithms;Sparse matrices;Vectors
[60] S. O. Al-Jazzar and T. Al-naffouri "Relay self interference minimisation using tapped filter",  in 2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA), May 2013. [abstract] [.bib]

Abstract In this paper we introduce a self interference (SI) estimation and minimisation technique for amplify and forward relays. Relays are used to help forward signals between atransmitter and a receiver. This helps increase the signal coverage and reduce the required transmitted signal power. One problem that faces relays communications is the leaked signalfrom the relay's output to its input. This will cause an SI problem where the new received signal at the relay's input will be added with the unwanted leaked signal from the relay'soutput. A Solution is proposed in this paper to estimate and minimise this SI which is based upon using a tapped filter at the destination. To get the optimum weights for this tappedfilter, some channel parameters must be estimated first. This is performed blindly at the destination without the need of any training. This channel parameter estimation method isnamed the blind-self-interference-channel-estimation (BSICE) method. The next step in the proposed solution is to estimate the tapped filter's weights. This is performed by minimisingthe mean squared error (MSE) at the destination. This proposed method is named the MSE-Optimum Weight (MSE-OW) method. Simulation results are provided in this paper to verify theperformance of BSICE and MSE-OW methods.

Keywords: amplify and forward communication;channel estimation;filtering theory;interference suppression;mean square error methods;radio receivers;radio transmitters;BSICEperformance;MSE-OW methods;MSE-optimum weight method;amplify and forward relays;blind-self-interference-channel-estimation method;channel parameters;mean squared error;receiver;relayoutput;relay self interference minimisation;self interference estimation technique;self interference minimisation technique;tapped filter;transmitted signal power;transmitter;unwantedleaked signal;Channel estimation;Conferences;MIMO;Relays;Signal to noise ratio;Silicon;Wireless communication
[59] M. E. Eltayeb and H. R. Bahrami and T. Y. Al-Naffouri "On the efficiency and privacy of smart grids neighborhood area networks",  in 2013 IEEE Energytech, May 2013. [abstract] [.bib]

Abstract A key task of smart meters is to securely report the power consumption of households and provide dynamic pricing to consumers. While transmission to all meters can beperformed via a simple broadcast, several challenges are faced during the reporting process. Firstly, the communication network should be able to handle the large amount of loadreports, and secondly, the privacy of the load report should be ensured. In this paper, we propose a novel compressive sensing based network design that 1) reduces the communicationnetwork transmission overhead, and 2) ensures the privacy of the load reports. Based on recent findings from [1] and [2], numerical results show that the proposed design significantlyreduces the network transmission overhead and utilizes the fading channel to encrypt the load reports, thus making it almost impossible for an eavesdropper to decipher the loadreports.

Keywords: fading channels;smart meters;smart power grids;communication network transmission overhead;compressive sensing;dynamic pricing;eavesdropper;fading channel;neighborhood areanetworks;power consumption;smart grids;smart meters;Compressed sensing;Jamming;Power demand;Privacy;Smart grids;Throughput;Vectors;Compressive Sensing;Neighborhood AreaNetworks;Security;Smart Grids
[58] M. Masood and T. Y. Al-Naffouri "Support agnostic Bayesian matching pursuit for block sparse signals",  in 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2013. [abstract] [code] [.bib]


A fast matching pursuit method using a Bayesian approach is introduced for block-sparse signal recovery. This method performs Bayesian estimates of block-sparse signals evenwhen the distribution of active blocks is non-Gaussian or unknown. It is agnostic to the distribution of active blocks in the signal and utilizes a priori statistics of additive noiseand the sparsity rate of the signal, which are shown to be easily estimated from data and no user intervention is required. The method requires a priori knowledge of block partitionand utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE)estimate of the block-sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator.

Keywords: Bayes methods;compressed sensing;iterative methods;least mean squares methods;time-frequency analysis;Bayesian estimation;MMSE estimation;additive noise;agnostic Bayesianmatching pursuit;block partition;block sparse signal recovery;fast matching pursuit method;greedy approach;minimum mean square error estimation;order recursive update;Bayesmethods;Clustering algorithms;Greedy algorithms;Matching pursuit algorithms;Noise;Robustness;Vectors;Bayesian matching pursuit;Block sparse signals;SABMP;compressed sensing;sparsesignal recovery
[57] M. Omer and A. A. Quadeer and T. Y. Al-Naffouri and M. S. Sharawi "An L-shaped microphone array configuration for impulsive acoustic source localization in 2-D using orthogonal clustering based time delay estimation",  in 2013 1st International Conference on Communications, Signal Processing, and their Applications (ICCSPA), Feb 2013. [abstract] [.bib]


This paper presents an L-shaped microphone array configuration for a robust 2-D localization of an impulsive acoustic source in an indoor environment. The localizationtechnique relies on a recently proposed time delay estimation technique based on the orthogonal clustering algorithm (TDE-OC) which is designed to work under room reverberantconditions and at low sampling rates. The TDE-OC method finds the TDEs from the sparse room impulse response (RIR) signal. The TDE's obtained from RIR adds to the robustness of theTDE-OC method against room reverberations while the low sampling rates requirement reduces the hardware and computational complexity and relaxes the communication link between themicrophones and the centralized location. Experimental results show the robustness of this method in a reverberant environment with low sampling rates, when compared with thegeneralized cross correlation method.

Keywords: acoustic radiators;acoustic signal processing;estimation theory;microphone arrays;L-shaped microphone array configuration;TDE-OC method;centralized location;communicationlink;computational complexity;generalized cross correlation method;impulsive acoustic source localization;indoor environment;orthogonal clustering algorithm;robust 2D localization;roomreverberant conditions;room reverberations;sampling rates;sparse room impulse response signal;time delay estimation;Delay effects;Estimation;Microphones;Positionmeasurement;Reverberation;Robustness
[56] H. Ali and A. A. Quadeer and M. S. Sharawi and T. Y. Al-Naffouri "Investigating the effects of tuning parameters on the orthogonal clustering algorithm in time delay estimation",  in 2013 1st International Conference on Communications, Signal Processing, and their Applications (ICCSPA), Feb 2013. [abstract] [.bib]

Abstract Localization systems are most often based on time delay estimation (TDE) techniques. TDE techniques based on channel impulse response (CIR) are effective in reverberantenvironment such as indoors. A recently developed algorithm called Orthogonal Clustering (OC) algorithm is one such algorithm that estimates the CIR utilizing a sparse signalreconstruction approach. OC is based on low complexity Bayesian method utilizing the sparsity constraint, the sensing matrix structure and the a priori statistical information. Inpractical systems several parameters affect the performance of a localization system based on OC TDE. Therefore, it is necessary to analyze the performance of an algorithm when certainparameters vary. In this paper we investigate the effect of variations in different parameters on the performance of the OC algorithm used in an impulsive acoustic source localization(IASL) system.

Keywords: belief networks;matrix algebra;pattern clustering;signal reconstruction;statistical analysis;transient response;OC algorithm;TDE technique;a priori statisticalinformation;channel impulse response;impulsive acoustic source localization system;low complexity Bayesian method;orthogonal clustering algorithm;reverberant environment;sensing matrixstructure;sparsity constraint;time delay estimation;time delay estimation technique;tuning parameters;Clustering algorithms;Delay effects;Dictionaries;Estimation;Indexes;Positionmeasurement;Runtime
[55] Mudassir Masood and T. Y. Al-Naffouri "Non-Gaussian prior Fast Bayesian Matching Pursuit",  in 15th. Saudi Technical Exchange Meeting (STEM), Dec 2012. [.bib]
[54] Z. Saleem and S. Al-Ghadhban and T. Y. Al-Naffouri "On the use of blind source separation for peak detection in spectrum sensing",  in 2012 IEEE International Conference on Control System, Computing and Engineering, Nov 2012. [abstract] [.bib]

Abstract Applying wavelet edge detection technique on observed wideband spectrum, results in a signal which contains frequency band boundaries information. Resultant signal containspeaks at locations corresponding to frequency band boundaries i.e. start and end locations of frequency bands. In the presence of noise resultant signal contains mixture of true peaksand noisy peaks. A threshold value is required to extract true peaks efficiently from mixture. In this paper calculation of threshold value is performed using blind source separationtechnique. Probability of detection and success ratio plots are used to evaluate proposed technique. Success ratio plot shows improvement of 4 dB and probability of detection plotshows improvement of 8 dB. Moreover, the proposed algorithm is based on the received signal and does not require any apriori information.

Keywords: blind source separation;cognitive radio;edge detection;probability;radio spectrum management;signal denoising;signal detection;wavelet transforms;blind sourceseparation;cognitive radio;detection probability;frequency band boundary information;noise resultant signal;noisy peaks;peak detection;spectrum sensing;success ratio plots;thresholdvalue calculation;true peak extraction;wavelet edge detection technique;wideband spectrum;Blind Source Separation;Cognitive Radio;Edge Detection
[53] M. Omer and A. A. Quadeer and M. S. Sharawi and T. Y. Al-Naffouri "Time delay estimation in a reverberant environment by low rate sampling of impulsive acoustic sources",  in 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA), Jul 2012. [abstract] [.bib]

Abstract This paper presents a new method of time delay estimation (TDE) using low sample rates of an impulsive acoustic source in a room environment. The proposed method finds thetime delay from the room impulse response (RIR) which makes it robust against room reverberations. The RIR is considered a sparse phenomenon and a recently proposed sparse signalreconstruction technique called orthogonal clustering (OC) is utilized for its estimation from the low rate sampled received signal. The arrival time of the direct path signal at apair of microphones is identified from the estimated RIR and their difference yields the desired time delay. Low sampling rates reduce the hardware and computational complexity anddecrease the communication between the microphones and the centralized location. The performance of the proposed technique is demonstrated by numerical simulations and experimentalresults.

Keywords: acoustic signal processing;computational complexity;microphones;numerical analysis;signal reconstruction;signal sampling;RIR;TDE;computational complexity;hardwarecomplexity;impulsive acoustic sources;low rate sampled received signal;microphones;numerical simulations;orthogonal clustering;reverberant environment;room environment;room impulseresponse;room reverberations;sparse signal reconstruction technique;time delay estimation;Correlation;Delay effects;Estimation;Hardware;Microphones;Reverberation
[52] O. Rauf and A. A. Quadeer and M. S. Sharawi and T. Y. Al-Naffouri "RIR estimation using impulsive sources with sub-Nyquist sampling",  in Int. Conf. on Inform. Science, Signal Process. and their applications (ISSPA), Jul 2012. [.bib]
[51] E. B. Al-Safadi and T. Y. Al-Naffouri "Pilotless recovery of clipped OFDM signals by compressive sensing over reliable data carriers",  in 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Jun 2012. [abstract] [.bib]

Abstract In this paper we propose a novel method of clipping mitigation in OFDM using compressive sensing that completely avoids using reserved tones or channel-estimation pilots. Themethod builds on selecting the most reliable perturbations from the constellation lattice upon decoding at the receiver (in the frequency domain), and performs compressive sensing overthese observations in order to completely recover the sparse nonlinear distortion in the time domain. As such, the method provides a practical solution to the problem of initialerroneous decoding decisions in iterative ML methods, and the ability to recover the distorted signal in one shot.

Keywords: OFDM modulation;Rayleigh channels;compressed sensing;iterative decoding;maximum likelihood decoding;perturbation techniques;telecommunication signalling;clipped OFDMsignal;clipping mitigation;compressive sensing;constellation lattice;distorted signal recovery;frequency domain;initial erroneous decoding decision;iterative maximum likelihoodmethod;pilotless recovery;reliable data carrier;reliable perturbation;sparse nonlinear distortion;time domain;Compressed sensing;Decoding;Frequency domainanalysis;OFDM;Receivers;Reliability;Vectors
[50] M. S. Sohail and T. Y. Al-Naffouri and S. N. Al-Ghadhban "Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach",  in 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Jun 2012. [abstract] [.bib]

Abstract This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing(ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous with the frequency grid of the ZP-OFDM system. The proposed structure based technique uses the fact that theNBI signal is sparse as compared to the ZP-OFDM signal in the frequency domain. The structure is also useful in reducing the computational complexity of the proposed method. The paperalso presents a data aided approach for improved NBI estimation. The suitability of the proposed method is demonstrated through simulations.

Keywords: OFDM modulation;computational complexity;frequency-domain analysis;interference suppression;maximum likelihood estimation;radio networks;ML approach;NBI;ZP-OFDM signalsystem;computational complexity;frequency grid;frequency-domain analysis;narrow band interference cancelation;structured maximum likelihood approach;time variant;zero padded orthogonalfrequency division multiplexing system;Estimation;Frequency domain analysis;Interference;Noise;OFDM;Receivers;Vectors
[49] H. Ali , M. S. Sharawi and T. Y. Al-Naffouri "Error sources in COTS WSN platforms for impulsive signal acquisition applications",  in 2012 19th International Conference on Telecommunications (ICT), Apr 2012. [abstract] [.bib]


In this work we present a detailed discussion of the various sources of errors in commercial off the shelf (COTS) wireless sensor node (WSN) platforms through a series ofexperiments. These COTS WSNs are programmed using the TinyOS 2.x standard components and interfaces. The experimental setup is used to record an impulsive acoustic signal from severalsensor nodes' microphones and send to the base-station for processing. The Flooding Time Synchronization Protocol (FTSP) was used, and a special MATLAB interfacing code was written toanalyze and present the errors within this acquisition setup. It was found that there are at least 4 error sources that can dramatically degrade the signal acquisition due to the factthat standard TinyOS components are not suitable for medium/high sampling frequency applications.

Keywords: acoustic signal detection;impulse noise;operating systems (computers);protocols;telecommunication computing;wireless sensor networks;COTS WSN platform;FTSP;MATLAB interfacingcode;TinyOS;commercial off the shelf;error sources;flooding time synchronization protocol;impulsive acoustic signal;impulsive signal acquisition;wireless sensornode;Hardware;Microphones;Standards;Synchronization;Uncertainty;Wireless sensor networks;Writing;COTS;Error Sources;Impulsive Noise;Synchronization;WSN
[48] S. F. Ahmed and T. Y. Al-Naffouri and A. H. Muqaibel "Low-complexity MAP based channel support estimation for Impulse Radio Ultra-Wideband (IR-UWB) communications",  in 2011 IEEE International Conference on Ultra-Wideband (ICUWB), Sep 2011. [abstract] [.bib]

Abstract The paper addresses the problem of channel estimation in Impulse-Radio Ultra-Wideband (IR-UWB) communication system. The IEEE 802.15.4a channel model is used where thechannel is assumed to be Linear Time Invariant (LTI) and thus the problem of channel estimation becomes the estimation of the sparse channel taps and their delays. Since, the bandwidthof the signal is very large, Nyquist rate sampling is impractical, therefore, we propose to estimate the channel taps from the sub-sampled versions of the received signal profile. Weadopt the Bayesian framework to estimate the channel support by incorporating the a priori multipath arrival time statistics. In the first approach, we adopt a two-step method byemploying Compressive Sensing to obtain coarse estimates and then refine them by applying Maximum A Posteriori (MAP) criterion. In the second approach, we develop a Low-Complexity MAP(LC-MAP) estimator. The computational complexity is reduced by identifying nearly orthogonal clusters in the received profile and by leveraging the structure of the sensing matrix.

Keywords: Bayes methods;channel estimation;communication complexity;maximum likelihood estimation;ultra wideband communication;wireless channels;Bayesian framework;IEEE 802.15.4achannel model;IR-UWB communication;LC-MAP estimator;MAP criterion;a priori multipath arrival time statistics;compressive sensing;computational complexity;impulse radio ultra-widebandcommunication;linear time invariant;low-complexity MAP based channel support estimation;maximum a posteriori criterion;sensing matrix;signal bandwidth;sparse channeltaps;Bandwidth;Channel estimation;Compressed sensing;Delay;Estimation;Receivers;Ultra wideband technology
[47] A. A. Quadeer and S. F. Ahmed and T. Y. Al-Naffouri "Structure based Bayesian sparse reconstruction using non-Gaussian prior",  in 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Sep 2011. [abstract] [.bib]

Abstract In this paper, we present a fast Bayesian method for sparse signal recovery that makes a collective use of the sparsity information, a priori statistical properties, and thestructure involved in the problem to obtain near optimal estimates at very low complexity. Specifically, we utilize the rich structure present in the sensing matrix encountered in manysignal processing applications to develop a fast reconstruction algorithm when the statistics of the sparse signal are non- Gaussian or unknown. The proposed method outperforms thewidely used convex relaxation approaches as well as greedy matching pursuit techniques all while operating at a much lower complexity.

Keywords: Bayes methods;Gaussian processes;convex programming;greedy algorithms;iterative methods;signal reconstruction;statistics;time-frequency analysis;convex relaxationapproach;greedy matching pursuit technique;matrix sensing;nonGaussian sparse signal;optimal estimation;signal processing application;signal reconstruction;sparse signal recoveryinformation;statistical property;structure based Bayesian sparse reconstruction algorithm;Computational complexity;Correlation;Discrete Fourier transforms;Minimization;Sensors;Sparsematrices;Vectors
[46] T. Y. Al-Naffouri and A. A. Quadeer and G. Caire "Impulsive noise estimation and cancellation in DSL using orthogonal clustering",  in 2011 IEEE International Symposium on Information Theory Proceedings, Jul 2011. [abstract] [.bib]

Abstract Impulsive noise is the bottleneck that limits the distance at which DSL communications can take place. By considering impulsive noise a sparse vector, recently developedsparse reconstruction algorithms can be utilized to combat it. We propose an algorithm that utilizes the guard band null carriers for the impulsive noise estimation and cancellation.Instead of relying on â„“1 minimization as done in some popular general-purpose compressive sensing (CS) schemes, the proposed method exploits the structure present in the problem andthe available a priori information jointly for sparse signal recovery. The computational complexity of the proposed algorithm is very low as compared to the sparse reconstructionalgorithms based on â„“1 minimization. A performance comparison of the proposed method with other techniques, including â„“1 minimization and another recently developed scheme for sparsesignal recovery, is provided in terms of achievable rates for a DSL line with impulse noise estimation and cancellation.

Keywords: digital subscriber lines;interference suppression;minimisation;signal reconstruction;â„“1 minimization;DSL;DSL communications;impulsive noise cancellation;impulsive noiseestimation;orthogonal clustering;sparse reconstruction algorithms;sparse signal recovery;Complexity theory;DSL;Estimation;Matching pursuitalgorithms;Minimization;Noise;OFDM;DSL;Impulsive noise;Sparse signal reconstruction;and Compressive sensing
[45] K. M. Z. Islam and T. Y. Al-Naffouri and N. Al-Dhahir "Asymptotically MMSE-optimum pilot design for comb-type OFDM channel estimation in high-mobility scenarios",  in 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2011. [abstract] [.bib]

Abstract Under high mobility, the orthogonality between sub-carriers in an OFDM symbol is destroyed resulting in severe inter-carrier interference (ICI). We present a novel algorithmto estimate the channel and ICI coefficients by exploiting the channel's time and frequency correlations and the (approximately) banded structure of the frequency-domain channelmatrix. In addition, we invoke the asymptotic equivalence of Toeplitz and circulant matrices to reduce the dimensionality of the channel estimation problem by retaining the dominantterms only in an offline eigen-decomposition. Furthermore, we show that the asymptotically MMSE-optimum pilot design consists of identical equally-spaced frequency-domain clusterswhose size is determined by the channel Doppler spread. Comparisons of our proposed algorithm with a widely-cited recent algorithm demonstrate a significant performance advantage at acomparable real-time complexity.

Keywords: Algorithm design and analysis;Approximation algorithms;Channel estimation;Clustering algorithms;Covariance matrix;Frequency domain analysis;OFDM;Channel estimation;Dopplerfrequency;ICI;Model reduction;OFDM
[44] T. Y. Al-Naffouri and F. F. Al-Shaalan and A. A. Quadeer and H. Hmida "Impulsive noise estimation and cancellation in DSL using compressive sampling",  in 2011 IEEE International Symposium of Circuits and Systems (ISCAS), May 2011. [abstract] [.bib]

Abstract Impulsive noise is the bottleneck that determines the maximum length of the DSL. Impulsive noise seldom occurs in DSL but when it occurs, it is very destructive and resultsin dropping the affected DSL symbols at the receiver as they cannot be recovered. By considering impulsive noise a sparse vector, recently developed sparse reconstruction algorithmscan be utilized to combat it. We propose an algorithm that utilizes the null carriers for the impulsive noise estimation and cancellation. Specifically, we use compressive sampling fora coarse estimate of the impulse position, an a priori information based MAP metric for its refinement, followed by MMSE estimation for estimating the impulse amplitudes. We alsopresent a comparison of the achievable rate in DSL using our algorithm and recently developed algorithms for sparse signal reconstruction.

Keywords: digital subscriber lines;impulse noise;interference suppression;least mean squares methods;signal denoising;signal reconstruction;signal sampling;DSL symbol;MAP metric;MMSEestimation;coarse estimation;compressive sampling;impulse amplitude estimation;impulse position;impulsive noise cancellation;impulsive noise estimation;null carrier;sparse signalreconstruction algorithm;sparse vector;DSL;Estimation;Frequency domain analysis;Noise;OFDM;Receivers;Time domain analysis;Compressive sampling;DSL;Impulsive noise;Sparse signalreconstruction
[43] M. Moinuddin ,T. Y. Al-Naffouri and M. S. Sohail "Exact Tracking Analysis of the ∈-NLMS algorithm for circular complex correlated Gaussian input",  in The 10th IEEE International Symposium on Signal Processing and Information Technology, Dec 2010. [abstract] [.bib]


This work presents exact tracking analysis of the ∈-normalized least mean square (∈-NLMS) algorithm for circular complex correlated Gaussian input. The analysis is based onthe derivation of a closed form expression for the cumulative distribution function (CDF) of random variables of the form [∥ui∥(D1)2][دµ+∥ui∥(D2)2]-1. The CDF is then used to derive thefirst and second moments of these variables. These moments in turn completely characterize the tracking performance of the ∈-NLMS algorithm in explicit closed form expressions.Consequently, new explicit closed-form expressions for the steady state tracking excess mean square error and optimum step size are derived. The simulation results of the trackingbehavior of the filter match the expressions obtained theoretically for various degrees of input correlation and for various values of ∈.

Keywords: Gaussian processes;correlation methods;higher order statistics;least mean squares methods;random processes;target tracking;∈-NLMS algorithm;∈-normalized least mean squarealgorithm;CDF;circular complex correlated gaussian input;cumulative distribution function;exact tracking analysis;random variable;steady state tracking;Gold;Variable speeddrives;Adaptive algorithms;indefinite quadratic forms;tracking performance

H. Abeida and T. Y. Al-Nafouri

"Data-aided DOA estimation of single source with time-variant Rayleigh amplitudes",  in 2010 18th European Signal Processing Conference, Aug 2010. [abstract] [.bib]


This paper focuses on the data-aided (DA) direction of arrival (DOA) estimation of a single narrow-band source in time-varying Rayleigh fading amplitude. The time-variant fading amplitude is modeled by considering the Jakes' and the first order autoregressive (AR1) correlation models. Closed-form expressions of the CRB for DOA alone are derived for fast and slow Rayleigh fading amplitude. As a special case, the CRB under uncorrelated fading Rayleigh channel is derived. A analytical approximate expressions of the CRB are derived for low and high SNR that enable the derivation of a number of properties that describe the bound's dependence on key parameters such as SNR, channel correlation. A high signal-to-noise-ratio maximum likelihood (ML) estimator based on the AR1 correlation model is derived. The main objective is to reduce algorithm complexity to a single-dimensional search on the DOA parameter alone as in the static-channel DOA estimator. Finally, simulation results illustrate the performance of the estimator and confirm the validity of the theoretical analysis.

Keywords: Rayleigh channels;channel estimation;direction-of-arrival estimation;maximum likelihood estimation;channel correlation;data-aided DOA estimation;direction of arrival estimation;fading Rayleigh channel;first order autoregressive correlation models;maximum likelihood estimator;single narrow-band source;time-variant Rayleigh amplitudes;time-variant fading amplitude;Correlation;Direction-of-arrival estimation;Maximum likelihood estimation;Rayleigh channels;Signal to noise ratio;AR1 channel model;Cramأ©r Rao bound;DOA estimation;Jakes' channel model;ML estimator;Time-varying fading channel
[41] A. A. Quadeer and T. Y. Al-Naffouri "ML blind channel estimation in OFDM using cyclostationarity and spectral factorization",  in 2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Jun 2010. [abstract] [.bib]

Abstract Channel estimation is vital in OFDM systems for efficient data recovery. In this paper, we propose a blind algorithm for channel estimation that is based on the assumptionthat the transmitted data in an OFDM system is Gaussian (by central limit arguments). The channel estimate can then be obtained by maximizing the output likelihood function.Unfortunately, the likelihood function turns out to be multi-modal and thus finding the global maxima is challenging. We rely on spectral factorization and the cyclostationarity of theoutput to obtain the correct channel zeros. The Genetic algorithm is then used to fine tune the obtained solution.

Keywords: OFDM modulation;channel estimation;genetic algorithms;matrix decomposition;maximum likelihood estimation;statistical analysis;ML blind channelestimation;OFDM;cyclostationarity;genetic algorithm;likelihood function;spectral factorization;Heating;Indexes;OFDM;Blind channel estimation;Genetic algorithm;Maximum likelihoodestimation;Spectral factorization

H. Abeida and T. Y. Al-Nafouri and S. Al-Ghadhban

"Data-aided SNR estimation in time-variant Rayleigh fading channels",  in 2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Jun 2010. [abstract] [.bib]


This paper addresses the data-aided signal-to-noise ratio (SNR) estimation in time-variant flat Rayleigh fading channels. The time-variant fading channel is modeled by considering the Jakes' model and the first order autoregressive (AR1) model. Closed-form expressions of the Crameجپr-Rao bound (CRB) for data-aided SNR estimation are derived for fast and slow fading Rayleigh channels. As a special case, the CRB under uncorrelated fading Rayleigh channel is derived. Analytical approximate expressions of the CRB are derived for low and high SNR that enable the derivation of a number of properties that describe the bound's dependence on key parameters such as SNR, channel correlation, sample number. Since the exact maximum likelihood (ML) estimator is computationally intensive in the case of fast-fading channel, two approximate solutions are proposed for high and low SNR cases. Numerical results illustrate the performance of the estimators and confirm the validity of the theoretical analysis.

Keywords: Rayleigh channels;autoregressive processes;correlation methods;maximum likelihood estimation;signal processing;CRB;Crameجپr-Rao bound;ML estimator;analytical approximate expressions;autoregressive model;channel correlation;closed-form expressions;data-aided SNR estimation;data-aided signal-to-noise ratio estimation;fast-fading channel;maximum likelihood estimator;sample number;time-variant Rayleigh fading channels;Artificial neural networks;Signal to noise ratio;AR1 channel model;Cramأ©r Rao bound;Jakes channel model;ML estimator;SNR estimation;Time-varying fading channel
[39] S. T. Qaseem and T. Y. Al-Naffouri "Compressive Sensing for Reducing Feedback in MIMO Broadcast Channels",  in 2010 IEEE International Conference on Communications, May 2010. [abstract] [.bib]

Abstract We propose a generic feedback channel model, and compressive sensing based opportunistic feedback protocol for feedback resource (channels) reduction in MIMO BroadcastChannels under the assumption that both feedback and downlink channels are noisy and undergo block Rayleigh fading. The feedback resources are shared and are opportunistically accessedby users who are strong (users above a certain fixed threshold). Strong users send same feedback information on all shared channels. They are identified by the base station viacompressive sensing. The proposed protocol is shown to achieve the same sum-rate throughput as that achieved by dedicated feedback schemes, but with feedback channels growing onlylogarithmically with number of users.

Keywords: Access protocols;Base stations;Broadcasting;Channel state information;Communications Society;Downlink;MIMO;Rayleigh channels;State feedback;Throughput
[38] S. T. Qaseem and T. Y. Al-Naffouri and S. Alghadhban "Compressive sensing for feedback reduction in MIMO broadcast channels",  in 2010 17th International Conference on Telecommunications, Apr 2010. [abstract] [.bib]

Abstract We propose a generic feedback channel model, and compressive sensing based opportunistic feedback protocol for feedback resource (channels) reduction in MIMO BroadcastChannels under the assumption that both feedback and downlink channels are noisy and undergo block Rayleigh fading. The feedback resources are shared and are opportunistically accessedby users who are strong (users above a certain fixed threshold). Strong users send same feedback information on all shared channels. They are identified by the base station viacompressive sensing. The proposed protocol is shown to achieve the same sum-rate throughput as that achieved by dedicated feedback schemes, but with feedback channels growing onlylogarithmically with number of users.

Keywords: MIMO communication;broadcast channels;protocols;2010 feedback resource reduction;MIMO broadcast channels;Rayleigh fading;compressive sensing;feedback channels;feedbackinformation;generic feedback channel model;opportunistic feedback protocol;Access protocols;Base stations;Broadcasting;Channel state information;Downlink;MIMO;Rayleighchannels;Receiving antennas;State feedback;Transmitting antennas
[37] T. Y. Al-Naffouri and A. A. Quadeer "Blind channel estimation in OFDM systems by relying on the Gaussian assumption of the input",  in 2009 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Dec 2009. [abstract] [.bib]

Abstract In an OFDM system, the receiver requires an estimate of the channel to recover the transmitted data. Most channel estimation methods rely on some form of training whichreduces the useful data rate. In this paper, we introduce an algorithm that blindly estimates the channel by maximizing the log likelihood of the channel given the output data. Findingthe likelihood function of a linear system can be very difficult. However, in the OFDM case, central limit arguments can be used to argue that the time-domain input is Gaussian. Thistogether with the Gaussian assumption on the noise makes the output data Gaussian. The output likelihood function can then be maximized to obtain the maximum likelihood (ML) estimateof the channel. Unfortunately, this optimization problem is not convex and thus finding the global maximum is challenging. In this paper, we propose two methods to find the globalmaximum of the ML objective function. One is the blind Genetic algorithm and the other is the semi-blind Steepest descent method. The performance of the proposed algorithms isdemonstrated by computer simulations.

Keywords: Gaussian processes;OFDM modulation;channel estimation;genetic algorithms;maximum likelihood estimation;Gaussian assumption of the input;OFDM systems;blind channelestimation;blind genetic algorithm;computer simulations;linear system;log likelihood;maximum likelihood estimate;output likelihood function;semi-blind steepest descent method;Blindequalizers;Channel estimation;Digital video broadcasting;Frequency conversion;Linear systems;Maximum likelihood estimation;Minerals;OFDM;Petroleum;Time domain analysis;Blind channelestimation;Gaussian assumption on data;Maximum likelihood estimation;Semi-blind channel estimation
[36] E. B. Al-Safadi and T. Y. Al-Naffouri "On Reducing the Complexity of Tone-Reservation Based PAPR Reduction Schemes by Compressive Sensing",  in GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference, Nov 2009. [abstract] [.bib]

Abstract In this paper, we describe a novel design of a Peak-to-Average-Power-Ratio (PAPR) reducing system, which exploits the relative temporal sparsity of Orthogonal FrequencyDivision Multiplexed (OFDM) signals to detect the positions and amplitudes of clipped peaks, by partial observation of their frequency content at the receiver. This approach usesrecent advances in reconstruction of sparse signals from rank-deficient projections using convex programming collectively known as compressive sensing. Since previous work in theliterature has focused on using the reserved tones as spectral support for optimum peak-reducing signals in the time-domain, the complexity at the transmitter was always a problem. Inthis work, we alternatively use extremely simple peak-reducing signals at the transmitter, then use the reserved tones to detect the peak-reducing signal at the receiver by a convexrelaxation of an other-wise combinatorially prohibitive optimization problem. This in effect completely shifts the complexity to the receiver and drastically reduces it from a functionof N (the number of subcarriers in the OFDM signal), to a function of m (the number of reserved tones) which is a small subset of N.

Keywords: OFDM modulation;mathematical programming;receivers;signal detection;signal reconstruction;transmitters;OFDM signals;PAPR reduction;compressive sensing;convexprogramming;convex relaxation;orthogonal frequency division multiplexed;peak-to-average-power-ratio reducing system;receiver;signal detection;sparse signalsreconstruction;tone-reservation complexity;transmitter;Frequency estimation;Minerals;Nonlinear distortion;OFDM;Peak to average power ratio;Petroleum;Signal design;Signal detection;Timedomain analysis;Transmitters
[35] S. T. Qaseem and T. Y. Al-Naffouri and T. M. Al-Murad "Compressive sensing based opportunistic protocol for exploiting multiuser diversity in wireless networks",  in 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, Sep 2009. [abstract] [.bib]

Abstract A key feature in the design of any MAC protocol is the throughput it can provide. In wireless networks, the channel of a user is not fixed but varies randomly. Thus, in orderto maximize the throughput of the MAC protocol at any given time, only users with large channel gains should be allowed to transmit. In this paper, a compressive sensing basedopportunistic protocol for exploiting multiuser diversity in wireless networks is proposed. This protocol is based on the traditional protocol of R-ALOHA which allows users to competefor channel access before reserving the channel to the best user. We use compressive sensing to find the best user, and show that the proposed protocol requires less time forreservation and so it outperforms other schemes proposed in the literature. Also, as the proposed scheme requires less reservation time, it can be seen as an enhancement for R-ALOHAschemes in fast fading environment.

Keywords: access protocols;fading channels;multi-access systems;radio networks;MAC protocol;R-ALOHA;channel access;compressive sensing;multiuser diversity;opportunisticprotocol;wireless networks;Access protocols;Diversity reception;Downlink;Fading;Frequency estimation;Media Access Protocol;Throughput;Time measurement;Wireless applicationprotocol;Wireless networks;Compressed sensing;opportunistic communications;protocols;random access;reservation ALOHA;scheduling;wireless networks
[34] T. Y. Al-Naffouri "Frequency domain estimation of time varying channels in OFDMA systems: An EM approach",  in 2009 16th International Conference on Digital Signal Processing, Jul 2009. [abstract] [.bib]

Abstract OFDM modulation combines advantages of high achievable data rates and relatively easy implementation. However, for proper recovery of input, the OFDM receiver needs accuratechannel information. Most algorithms proposed in literature perform channel estimation in time domain which increases computational complexity in multi-access situations where the useris only interested in part of the spectrum. In this paper, we propose a frequency domain algorithm for channel estimation in OFDMA systems. The algorithm performs eigenvaluedecomposition of channel autocorrelation matrix and approximates channel frequency response seen by each user using the first few dominant eigenvectors. In a time variant environment,we derive a state space model for the evolution of the eigenmodes that help us to track them. This is done using a forward backward Kalman filter. The performance of the algorithm isfurther improved by employing a data-aided approach (based on expectation maximization).

Keywords: Kalman filters;OFDM modulation;channel estimation;computational complexity;eigenvalues and eigenfunctions;expectation-maximisation algorithm;frequency division multipleaccess;frequency response;matrix algebra;time-varying channels;EM approach;OFDM modulation;OFDMA systems;channel autocorrelation matrix;channel estimation;channel frequencyresponse;computational complexity;data-aided approach;eigenvalue decomposition;expectation maximization;forward backward Kalman filter;frequency domain estimation;multi-accesssituations;time varying channels;Autocorrelation;Channel estimation;Computational complexity;Eigenvalues and eigenfunctions;Frequency domain analysis;Frequency estimation;Frequencyresponse;Matrix decomposition;OFDM modulation;Time varying systems;Channel estimation;Kalman filtering;OFDMA;iterative methods;reduced order systems
[33] B. H. Khan and M. Debbah and O. Ryan and T. Y. Al-Naffouri "Estimation of the distribution of randomly deployed wireless sensors",  in 2009 IEEE International Symposium on Information Theory, Jun 2009. [abstract] [.bib]

Abstract The distribution of randomly deployed wireless sensors plays an important role in the quality of the methods used for data acquisition and signal reconstruction.Mathematically speaking, the estimation of the distribution of randomly deployed sensors can be related to computing the spectrum of Vandermonde matrices with non-uniform entries. Inthis paper, we use the recent free deconvolution framework to recover, in noisy environments, the asymptotic moments of the structured random Vandermonde matrices and relate thesemoments to the distribution of the randomly deployed sensors. Remarkably, the results are valid in the finite case using only a limited number of sensors and samples.

Keywords: matrix algebra;wireless sensor networks;asymptotic moments;data acquisition;deconvolution framework;non-uniform entries;randomly deployed wireless sensors;signalreconstruction;structured random Vandermonde matrices;Additive white noise;Deconvolution;Gaussian noise;Minerals;Petroleum;Signal reconstruction;Temperature measurement;Temperaturesensors;Wireless sensor networks;Working environment noise
[32] T. Y. Al-Naffouri and B. Hassibi "On the distribution of indefinite quadratic forms in Gaussian random variables",  in 2009 IEEE International Symposium on Information Theory, Jun 2009. [abstract] [.bib]

Abstract In this work, we propose a transparent approach to evaluating the CDF of indefinite quadratic forms in Gaussian random variables and ratios of such forms. This quantityappears in the analysis of different receivers in communication systems and in various applications in signal processing. Instead of attempting to find the pdf of this quantity as isthe case in many papers in literature, we focus on finding the CDF. The basic trick that we implement is to replace inequalities that appear in the CDF calculations with the unit stepfunction and replace the latter with its Fourier transform. This produces a multi-dimensional integral that can be evaluated using complex integration. We show how our approach extendsto nonzero mean Gaussian real/complex vectors and to the joint distribution of indefinite quadratic forms.

Keywords: Fourier transforms;Gaussian distribution;integration;Fourier transform;Gaussian random variables;complex integration;cumulative distribution function;indefinite quadraticforms;Algorithm design and analysis;Communication systems;Diversity reception;Fourier transforms;Information theory;Minerals;Multidimensional signal processing;Petroleum;Randomvariables;Signal analysis
[31] T. Y. Al-Naffouri and M. E. El-Tayeb "Opportunistic beamforming with precoding for spatially correlated channels",  in 2009 11th Canadian Workshop on Information Theory, May 2009. [abstract] [.bib]

Abstract Random beamforming (RBF) exploits multiuser diversity to increase the sum-rate capacity of MIMO broadcast channels. However, in the presence of spatial correlation betweenthe downlink channels, multiuser diversity can not be exploited and the sum-rate suffers a signal to noise (SNR) hit. In this paper, we explore precoding techniques that minimize thishit. Basically, we derive an optimum and an approximate precoding matrix that minimizes the sum-rate hit of RBF. As a by product, we introduce a technique that evaluates the cumulativedistribution function (CDF) of weighted norms of Gaussian random variables.

Keywords: Gaussian channels;MIMO communication;antenna arrays;array signal processing;broadcast channels;channel capacity;channel coding;correlation methods;higher orderstatistics;matrix algebra;multiuser channels;precoding;random processes;wireless channels;CDF scheme;Gaussian random variable;MIMO broadcast channel;approximate precodingmatrix;cumulative distribution function;downlink channel;multiple antenna;multiuser diversity;precoding technique;random beamforming;spatially correlated channel;sum-ratecapacity;wireless system;Array signal processing;Broadcasting;Covariance matrix;Feedback;MIMO;Minerals;Petroleum;Random variables;Receiving antennas;Transmitting antennas
[30] A. A. Quadeer and T. Y. Al-Naffouri and M. Shadaydeh "Iterative blind data detection in constant modulus OFDM systems",  in 2008 16th European Signal Processing Conference, Aug 2008. [abstract] [.bib]

Abstract In this paper, we consider blind data detection for OFDM transmission over block fading channels. Specifically, we show how constant modulus data of an OFDM symbol can beblindly detected using output symbol and associated cyclic prefix. Our approach relies on decomposing the OFDM channel into two subchannels (cyclic and linear) that share the sameinput and are characterized by the same channel parameters. This fact enables us to estimate the channel parameters from one subchannel and substitute the estimate into the other, thusobtaining a nonlinear relationship involving the input and output data only that can be searched for the maximum likelihood estimate of the input. This shows that OFDM systems arecompletely identifiable using output data only, irrespective of the channel zeros, as long as the channel delay spread is less than the length of the cyclic prefix. We also proposeiterative methods to reduce the computational complexity involved in the maximum likelihood search of input.

Keywords: OFDM modulation;computational complexity;fading channels;iterative methods;maximum likelihood estimation;OFDM channel;OFDM symbol;OFDM transmission;block fadingchannels;channel parameters;channel zeros;computational complexity;constant modulus OFDM systems;cyclic prefix;cyclic subchannel;iterative blind data detection;linearsubchannel;maximum likelihood estimation;Channel estimation;Complexity theory;Estimation;OFDM;Signal to noise ratio;Training;Vectors
[29] G. Caire and T. Y. Al-Naffouri and A. K. Narayanan "Impulse noise cancellation in OFDM: an application of compressed sensing",  in 2008 IEEE International Symposium on Information Theory, Jul 2008.