Tareq Y. Al-Naffouri

King Fahd University of Petroleum and Minerals, Az̧ Z̧ahrān, Eastern Province, Saudi Arabia

Are you Tareq Y. Al-Naffouri?

Claim your profile

Publications (108)113.88 Total impact

  • Source
    [Show abstract] [Hide abstract]
    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 chal-lenges. Firstly, CSI acquisition generates a great 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. This could 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 feedback relay 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 with limited 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, we introduce 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 maximum equivalent 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 and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback channels.
    IEEE Globecom, Austin, TX, USA; 12/2014
  • Proceedings of IEEE GLOBECOM 2014; 12/2014
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper addresses the coordinated scheduling problem in cloud-enabled networks. Consider the downlink of a cloud-radio access network (C-RAN), where the cloud is only responsible 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 several time/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 across the 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 more power-zone 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 an association 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 that vertex. The paper further presents heuristic algorithms with low computational complexity. Simulation results show the performance of the proposed algorithms and suggest that the heuristics perform near optimal in low shadowing environments
    11/2014;
  • Source
    Anum Ali, Abdullatif Al-Rabah, Mudassir Masood, Tareq Y. Al-Naffouri
    [Show abstract] [Hide abstract]
    ABSTRACT: Clipping is one of the simplest peak-to-average power ratio (PAPR) reduction schemes for orthogonal frequency division multiplexing (OFDM). Deliberately clipping the transmission signal degrades system performance, and clipping mitigation is required at the receiver for information restoration. In this work, we acknowledge the sparse nature of the clipping signal and propose a low-complexity Bayesian clipping estimation scheme. The proposed scheme utilizes a priori information about the sparsity rate and noise variance for enhanced recovery. At the same time, the proposed scheme is robust against inaccurate estimates of the clipping signal statistics. The undistorted phase property of the clipped signal, as well as the clipping likelihood, is utilized for enhanced reconstruction. Further, motivated by the nature of modern OFDM-based communication systems, we extend our clipping reconstruction approach to multiple antenna receivers, and multi-user OFDM. We also address the problem of channel estimation from pilots contaminated by the clipping distortion. Numerical findings are presented, that depict favourable results for the proposed scheme compared to the established sparse reconstruction schemes.
    IEEE Access. 10/2014; 2.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a novel narrowband interference (NBI) mitigation scheme for SC-FDMA systems. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a low complexity Bayesian sparse recovery procedure. At the transmitter, a few randomly chosen sub-carriers are kept data free to sense the NBI signal at the receiver. Further, it is noted that in practice, the sparsity of the NBI signal is destroyed by a grid mismatch between NBI sources and the system under consideration. Towards this end, first an accurate grid mismatch model is presented that is capable of assuming independent offsets for multiple NBI sources. Secondly, prior to NBI reconstruction, the sparsity of the unknown signal is restored by employing a sparsifying transform. To improve the spectral efficiency of the proposed scheme, a data-aided NBI recovery procedure is outlined that relies on adaptively selecting a subset of data carriers and uses them as additional measurements to enhance the NBI estimation. Finally, the proposed scheme is extended to single-input multi-output systems by performing a collaborative NBI support search over all antennas. Numerical results are presented that depict the suitability of the proposed scheme for NBI mitigation.
    10/2014;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we consider the problem of reducing the broadcast decoding delay of instantly decodable network coding (IDNC) for device-to-device (D2D) communication in wireless network. In this configuration, users in the network can help hasten the recovery of the lost packets of users in their transmission range by sending network coded packets. In order to solve this problem, we first identify the different events for each user and used them to derive an expression for the probability distribution of the decoding delay used in the formulation of the cooperative problem. The optimal solution when no interference is allowed between the transmitting users is expressed using a cooperative graph formulation. Through extensive simulations, we compare the decoding delay experienced by all users in the Point to Multi-Point (PMP) configuration, the full connected D2D (FC-D2D) configuration and our partially connected D2D (PC-D2D) configuration. Numerical results show that the PC-D2D outperforms the FC-D2D in all situation and provide a huge gain when the network is poorly connected.
    09/2014;
  • Source
    Mudassir Masood, Laila H. Afify, Tareq Y. Al-Naffouri
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper addresses the problem of estimating sparse channels in massive MIMO-OFDM systems. Most wireless channels are sparse in nature with large delay spread. In addition, these channels as observed by multiple antennas in a neighborhood have approximately common support. The sparsity and common support properties are attractive when it comes to the efficient estimation of large number of channels in massive MIMO systems. Moreover, to avoid pilot contamination and to achieve better spectral efficiency, it is important to use a small number of pilots. We present a novel channel estimation approach which utilizes the sparsity and common support properties to estimate sparse channels and require a small number of pilots. Two algorithms based on this approach have been developed which perform Bayesian estimates of sparse channels even when the prior is non-Gaussian or unknown. Neighboring antennas share among each other their beliefs about the locations of active channel taps to perform estimation. The coordinated approach improves channel estimates and also reduces the required number of pilots. Further improvement is achieved by the data-aided version of the algorithm. Extensive simulation results are provided to demonstrate the performance of the proposed algorithms.
    IEEE Transactions on Signal Processing 09/2014; 63(1). · 3.20 Impact Factor
  • M.E. Eltayeb, Tareq Y. Al-Naffouri, H.R. Bahrami
    [Show abstract] [Hide abstract]
    ABSTRACT: In multi-antenna broadcast networks, the base stations (BSs) rely on the channel state information (CSI) of the users to perform user scheduling and downlink transmission. However, in networks with large number of users, obtaining CSI from all users is arduous, if not impossible, in practice. This paper proposes channel feedback reduction techniques based on the theory of compressive sensing (CS), which permits the BS to obtain CSI with acceptable recovery guarantees under substantially reduced feedback overhead. Additionally, assuming noisy CS measurements at the BS, inexpensive ways for improving post-CS detection are explored. The proposed techniques are shown to reduce the feedback overhead, improve CS detection at the BS, and achieve a sum-rate close to that obtained by noiseless dedicated feedback channels.
    IEEE Transactions on Communications 09/2014; 62(9):3209-3222. · 1.98 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a robust method for two-dimensional (2D) impulsive acoustic source localization in a room environment using low sampling rates. The proposed method finds the time delay from the room impulse response (RIR) which makes it robust against room reverberations. We consider the RIR as a sparse phenomenon and apply a recently proposed sparse signal reconstruction technique called orthogonal clustering (OC) for its estimation from the sub-sampled received signal. The arrival time of the direct path signal at a pair of microphones is identified from the estimated RIR, and their difference yields the desired time delay estimate (TDE). Low sampling rates reduces the hardware and computational complexity and decreases the communication between the microphones and the centralized location. Simulation and experimental results of an actual hardware setup are presented to demonstrate the performance of the proposed technique.
    EURASIP journal on advances in signal processing 07/2014; · 0.89 Impact Factor
  • Source
    Anum Ali, Ali Al-Zahrani, Tareq Y Al-Naffouri, Ayman Naguib
    [Show abstract] [Hide abstract]
    ABSTRACT: High peak-to-average power ratio is one of the major draw-backs of orthogonal frequency division multiplexing (OFDM). Clipping is the simplest peak reduction scheme, however, it requires clipping mitigation at the receiver. Recently com-pressed 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 fre-quency domain and one cannot distinguish between distor-tions from different users. In this work, a collaborative clip-ping removal strategy is proposed based on joint estimation of the clipping distortions from all users. Further, an effective data aided channel estimation strategy for clipped OFDM is also outlined. Simulation results are presented to justify the effectiveness of the proposed schemes.
    International Conference on Acoustics, Speech and Signal Processing (ICASSP); 05/2014
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we introduce a game theoretic framework for studying the problem of minimizing the delay of instantly decodable network coding (IDNC) for cooperative data exchange (CDE) in decentralized wireless network. In this configuration, clients cooperate with each other to recover the erased packets without a central controller. Game theory is 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 by self-interested players in a non-cooperative potential game. The utility functions are designed such that increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Nash bargaining solution. Three games are developed: the first aims to reduce the completion time, the second to reduce the maximum decoding delay and the third the sum decoding delay. We improve these formulations to include punishment policy upon collision occurrence and achieve the Nash bargaining solution. Through extensive simulations, our framework is tested against the best performance that could be found in the conventional point-to-multipoint (PMP) recovery process in numerous cases: first we simulate the problem with complete information. We, then, simulate with incomplete information and finally we test it in lossy feedback scenario. Numerical results show that our formulation with complete information largely outperforms the conventional PMP scheme in most situations and achieves a lower delay. They also show that the completion time formulation with incomplete information also outperforms the conventional PMP.
    04/2014;
  • Source
    [Show abstract] [Hide abstract]
    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 cooperative data exchange (CDE) in decentralized wireless network. In this configuration, clients cooperate with each other to recover the erased packets without a central controller. Game theory is 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 by self-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 a desirable system performance in a shared network environment and the Pareto optimal solution. Through extensive 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 that our formulation largely outperforms the conventional PMP scheme in most practical situations and achieves a lower delay.
    04/2014;
  • IEEE WCNC; 04/2014
  • Source
    [Show abstract] [Hide abstract]
    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 receivers and 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 to perform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize the sum decoding delay [1] 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 and outperforms 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 delay significantly improve the number of served receivers when they are subject to strict delay constraints.
    04/2014;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, compressed sensing techniques are proposed to linearize commercial power amplifiers driven by orthogonal frequency division multiplexing signals. The nonlinear distortion is considered as a sparse phenomenon in the time-domain, and three compressed sensing based algorithms are presented to estimate and compensate for these distortions at the receiver using a few and, at times, even no frequency-domain free carriers (i.e. pilot carriers). The first technique is a conventional compressed sensing approach, while the second incorporates a priori information about the distortions to enhance the estimation. Finally, the third technique involves an iterative data-aided algorithm that does not require any pilot carriers and hence allows the system to work at maximum bandwidth efficiency. The performances of all the proposed techniques are evaluated on a commercial power amplifier and compared. The error vector magnitude and symbol error rate results show the ability of compressed sensing to compensate for the amplifier's nonlinear distortions.
    Signal Processing 04/2014; 97:282–293. · 2.24 Impact Factor
  • Tareq Y. Al-Naffouri, Ahmed A. Quadeer, Giuseppe Caire
    [Show abstract] [Hide abstract]
    ABSTRACT: Orthogonal Frequency Division Multiplexing (OFDM) is a modulation scheme that is widely used in wired and wireless communication systems. While OFDM is ideally suited to deal with frequency selective channels and AWGN, its performance may be dramatically impacted by the presence of impulse noise. In fact, very strong noise impulses in the time domain might result in the erasure of whole OFDM blocks of symbols at the receiver. Impulse noise can be mitigated by considering it as a sparse signal in time, and using recently developed algorithms for sparse signal reconstruction. We propose an algorithm that utilizes the guard band null subcarriers for the impulse noise estimation and cancellation. Instead of relying on ell_1 minimization as done in some popular general-purpose compressive sensing schemes, the proposed method jointly exploits the specific structure of this problem and the available a priori information for sparse signal recovery. The computational complexity of the proposed algorithm is very competitive with respect to sparse signal reconstruction schemes based on ell_1 minimization. The proposed method is compared with respect to other state-of-the-art methods in terms of achievable rates for an OFDM system with impulse noise and AWGN.
    IEEE Transactions on Communications 03/2014; 62(3):976-989. · 1.98 Impact Factor
  • M.F.A. Ahmed, Tareq Y. Al-Naffouri, M.-S. Alouini, George Turkiyyah
    [Show abstract] [Hide abstract]
    ABSTRACT: Estimating unknown signal in Wireless Sensor Networks (WSNs) requires sensor nodes to transmit their observations of the signal over a multiple access channel to a Fusion Center (FC). The FC uses the received observations, which is corrupted by observation noise and both channel fading and noise, to find the minimum Mean Square Error (MSE) estimate of the signal. In this paper, we investigate the effect of the source-node correlation (the correlation between sensor node observations and the source signal) and the inter-node correlation (the correlation between sensor node observations) on the performance of the Linear Minimum Mean Square Error (LMMSE) estimator for three correlation models in the presence of channel fading. First, we investigate the asymptotic behavior of the achieved distortion (i.e., MSE) resulting from both the observation and channel noise in a non-fading channel. Then, the effect of channel fading is considered and the corresponding distortion outage probability, the probability that the distortion exceeds a certain value, is found. By representing the distortion as a ratio of indefinite quadratic forms, a closed-form expression is derived for the outage probability that shows its dependency on the correlation. Finally, the new representation of the outage probability allows us to propose an iterative solution for the power allocation problem to minimize the outage probability under total and individual power constraints. Numerical simulations are provided to verify our analytic results.
    IEEE Transactions on Signal Processing 12/2013; 61(24):6264-6275. · 3.20 Impact Factor
  • Source
    Anum Ali, Oualid Hammi, Tareq Y. Al-Naffouri
    [Show abstract] [Hide abstract]
    ABSTRACT: Linearization of user equipment power amplifiers driven by orthogonal frequency division multiplexing signals is addressed in this paper. Particular attention is paid to the power efficient operation of an orthogonal frequency division multiple access cognitive radio system and realization of such a system using compressed sensing. Specifically, precompensated overdriven amplifiers are employed at the mobile terminal. Over-driven amplifiers result in in-band distortions and out of band interference. Out of band interference mostly occupies the spectrum of inactive users, whereas the in-band distortions are mitigated using compressed sensing at the receiver. It is also shown that the performance of the proposed scheme can be further enhanced using multiple measurements of the distortion signal in single-input multi-output systems. Numerical results verify the ability of the proposed setup to improve error vector magnitude, bit error rate, outage capacity and mean squared error.
    Emerging and Selected Topics in Circuits and Systems, IEEE Journal on. 12/2013; 3(4):508-520.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we study the broadcast decoding delay performance of generalized instantly decodable network coding (G-IDNC) in the lossy feedback scenario. The problem is formulated as a maximum weight clique problem over the G-IDNC graph in [1]. In order to further minimize the decoding delay, we introduce in this paper the lossy G-IDNC graph (LG-IDNC). Whereas the G-IDNC graph represents only doubtless combinable packets, the LG-IDNC graph represents also uncertain packet combinations when the expected decoding delay of the encoded packet is lower than the individual expected decoding delay of each packet encoded in it. Since the maximum weight clique problem is known to be NP-hard, we use the heuristic introduced in [2] to discover the maximum weight clique in the LG-IDNC graph and finally we compare the decoding delay performance of LG-IDNC and G-IDNC graphs through extensive simulations. Numerical results show that our new LG-IDNC graph formulation outperforms the G-IDNC graph formulation in all situations and achieves significant improvement in the decoding delay especially when the feedback erasure probability is higher than the packet erasure probability.
    Wireless Communications Letters, IEEE. 11/2013; 3(3).
  • Mudassir Masood, Tareq Y. Al-Naffouri
    [Show abstract] [Hide abstract]
    ABSTRACT: A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data if not available. The method 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 sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator.
    IEEE Transactions on Signal Processing 11/2013; 61(21):5298-5309. · 3.20 Impact Factor

Publication Stats

595 Citations
113.88 Total Impact Points

Institutions

  • 2005–2014
    • King Fahd University of Petroleum and Minerals
      • Department of Electrical Engineering
      Az̧ Z̧ahrān, Eastern Province, Saudi Arabia
  • 2007
    • California Institute of Technology
      • Department of Electrical Engineering
      Pasadena, CA, United States
  • 1998–2004
    • Stanford University
      • Department of Electrical Engineering
      Stanford, CA, United States
    • Georgia Institute of Technology
      • School of Electrical & Computer Engineering
      Atlanta, GA, United States
  • 2001
    • University of California, Los Angeles
      • Department of Electrical Engineering
      Los Angeles, CA, United States