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AuthorAlouini, Mohamed-Slim (16)Amin, Osama (5)Al-Naffouri, Tareq Y. (3)Elsawy, Hesham (3)Randrianantenaina, Itsikiantsoa (3)View MoreDepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (23)Electrical Engineering Program (21)Applied Mathematics and Computational Science Program (1)EE, KAUST, Thuwal, N/A Saudi Arabia 69000 (1)Entrepreneurship Center (1)View MoreJournalIEEE Access (3)IEEE Transactions on Wireless Communications (3)2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP) (2)2017 IEEE Wireless Communications and Networking Conference (WCNC) (2)IEEE Transactions on Vehicular Technology (2)View MorePublisherInstitute of Electrical and Electronics Engineers (IEEE) (19)Elsevier BV (1)Subject

Optimization (24)

Interference (6)Wireless communication (5)Cellular networks (4)Decoding (4)View MoreThesis/Dissertation AdvisorClaudel, Christian G. (2)Heidrich, Wolfgang (1)Laleg-Kirati, Taous-Meriem (1)Thesis/Dissertation ProgramElectrical Engineering (4)TypeArticle (12)Conference Paper (8)Dissertation (3)Thesis (1)Year (Issue Date)2018 (3)2017 (12)2016 (5)2015 (4)Item AvailabilityOpen Access (15)Metadata Only (9)

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Delay Reduction in Multi-Hop Device-to-Device Communication using Network Coding

Douik, Ahmed; Sorour, Sameh; Al-Naffouri, Tareq Y.; Yang, Hong Chuan; Alouini, Mohamed-Slim (IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 2018-08-22) [Article]

This paper considers the problem of reducing the broadcast decoding delay of wireless networks using instantly decodable network coding (IDNC) based device-to-device (D2D) communications. In contrast with previous works that assume a fully connected network, this paper investigates a partially connected configuration in which multiple devices are allowed to transmit simultaneously. To that end, the different events occurring at each device are identified so as to derive an expression for the probability distribution of the decoding delay. Afterward, the joint optimization problem over the set of transmitting devices and packet combination of each is formulated. The optimal solution of the joint optimization problem is derived using a graph theoretic approach by introducing the cooperation graph in which each vertex represents a transmitting device with a weight translating its contribution to the network. The paper solves the problem by reformulating it as a maximum weight clique problem which can efficiently be solved. Numerical results suggest that the proposed solution outperforms state-of-the-art schemes and provides significant gain, especially for poorly connected networks.

lp-Box ADMM: A Versatile Framework for Integer Programming

Wu, Baoyuan; Ghanem, Bernard (IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers (IEEE), 2018-06-11) [Article]

This paper revisits the integer programming (IP) problem, which plays a fundamental role in many computer vision and machine learning applications. The literature abounds with many seminal works that address this problem, some focusing on continuous approaches (e.g., linear program relaxation), while others on discrete ones (e.g., min-cut). However, since many of these methods are designed to solve specific IP forms, they cannot adequately satisfy the simultaneous requirements of accuracy, feasibility, and scalability. To this end, we propose a novel and versatile framework called <formula><tex>$l_p$</tex></formula>-box ADMM, which is based on two main ideas. (1) The discrete constraint is equivalently replaced by the intersection of a box and an <formula><tex>$l_p$</tex></formula>-norm sphere. (2) We infuse this equivalence into the ADMM (Alternating Direction Method of Multipliers) framework to handle the continuous constraints separately and to harness its attractive properties. More importantly, the ADMM update steps can lead to manageable sub-problems in the continuous domain. To demonstrate its efficacy, we apply it to an optimization form that occurs often in computer vision and machine learning, namely binary quadratic programming (BQP). In this case, the ADMM steps are simple, computationally efficient. Moreover, we present the theoretic analysis about the global convergence of the <formula><tex>$l_p$</tex></formula>-box ADMM through adding a perturbation with the sufficiently small factor <formula><tex>$\epsilon$</tex></formula> to the original IP problem. Specifically, the globally converged solution generated by <formula><tex>$l_p$</tex></formula>-box ADMM for the perturbed IP problem will be close to the stationary and feasible point of the original IP problem within <formula><tex>$O(\epsilon)$</tex></formula>. We demonstrate the applicability of <formula><tex>$l_p$</tex></formula>-box ADMM on three important applications: MRF energy minimization, graph matching, and clustering. Results clearly show that it significantly outperforms existing generic IP solvers both in runtime and objective. It also achieves very competitive performance to state-of-the-art methods designed specifically for these applications

Energy-Efficient Optimization for HARQ Schemes over Time-Correlated Fading Channels

Shi, Zheng; Ma, Shaodan; Yang, Guanghua; Alouini, Mohamed-Slim (IEEE Transactions on Vehicular Technology, Institute of Electrical and Electronics Engineers (IEEE), 2018-03-19) [Article]

Energy efficiency of three common hybrid automatic repeat request (HARQ) schemes including Type I HARQ, HARQ with chase combining (HARQ-CC) and HARQ with incremental redundancy (HARQ-IR), is analyzed and joint power allocation and rate selection to maximize the energy efficiency is investigated in this paper. Unlike prior literature, time-correlated fading channels is considered and two widely concerned quality of service (QoS) constraints, i.e., outage and goodput constraints, are also considered in the optimization, which further differentiates this work from prior ones. Using a unified expression of asymptotic outage probabilities, optimal transmission powers and optimal rate are derived in closed-forms to maximize the energy efficiency while satisfying the QoS constraints. These closed-form solutions then enable a thorough analysis of the maximal energy efficiencies of various HARQ schemes. It is revealed that with low outage constraint, the maximal energy efficiency achieved by Type I HARQ is <formula><tex>$\frac{1}{4\ln2}$</tex></formula> bits/J, while HARQ-CC and HARQ-IR can achieve the same maximal energy efficiency as <formula><tex>$\frac{\kappa_\infty}{4\ln2}$</tex></formula> bits/J where <formula><tex>$\kappa_\infty = 1.6617$</tex></formula>. Moreover, time correlation in the fading channels has a negative impact on the energy efficiency, while large maximal allowable number of transmissions is favorable for the improvement of energy efficiency. The effectiveness of the energy-efficient optimization is verified by extensive simulations and the results also show that HARQ-CC can achieve the best tradeoff between energy efficiency and spectral efficiency among the three HARQ schemes.

Bounded Perturbation Regularization for Linear Least Squares Estimation

Ballal, Tarig; Suliman, Mohamed Abdalla Elhag; Al-Naffouri, Tareq Y. (IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2017-10-18) [Article]

This paper addresses the problem of selecting the regularization parameter for linear least-squares estimation. We propose a new technique called bounded perturbation regularization (BPR). In the proposed BPR method, a perturbation with a bounded norm is allowed into the linear transformation matrix to improve the singular-value structure. Following this, the problem is formulated as a min-max optimization problem. Next, the min-max problem is converted to an equivalent minimization problem to estimate the unknown vector quantity. The solution of the minimization problem is shown to converge to that of the ℓ2 -regularized least squares problem, with the unknown regularizer related to the norm bound of the introduced perturbation through a nonlinear constraint. A procedure is proposed that combines the constraint equation with the mean squared error (MSE) criterion to develop an approximately optimal regularization parameter selection algorithm. Both direct and indirect applications of the proposed method are considered. Comparisons with different Tikhonov regularization parameter selection methods, as well as with other relevant methods, are carried out. Numerical results demonstrate that the proposed method provides significant improvement over state-of-the-art methods.

Non-Orthogonal Multiple Access for Large-Scale 5G Networks: Interference Aware Design

Ali, Konpal S.; Elsawy, Hesham; Chaaban, Anas; Alouini, Mohamed-Slim (IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2017-09-18) [Article]

Non-orthogonal multiple access (NOMA) is promoted as a key component of 5G cellular networks. As the name implies, NOMA operation introduces intracell interference (i.e., interference arising within the cell) to the cellular operation. The intracell interference is managed by careful NOMA design (e.g., user clustering and resource allocation) along with successive interference cancellation. However, most of the proposed NOMA designs are agnostic to intercell interference (i.e., interference from outside the cell), which is a major performance limiting parameter in 5G networks. This article sheds light on the drastic negative-impact of intercell interference on the NOMA performance and advocates interference-aware NOMA design that jointly accounts for both intracell and intercell interference. To this end, a case study for fair NOMA operation is presented and intercell interference mitigation techniques for NOMA networks are discussed. This article also investigates the potential of integrating NOMA with two important 5G transmission schemes, namely, full duplex and device-to-device communication. This is important since the ambitious performance defined by the 3rd Generation Partnership Project (3GPP) for 5G is foreseen to be realized via seamless integration of several new technologies and transmission techniques.

Improper signaling in two-path relay channels

Gaafar, Mohamed; Amin, Osama; Schaefer, Rafael F.; Alouini, Mohamed-Slim (2017 IEEE International Conference on Communications Workshops (ICC Workshops), Institute of Electrical and Electronics Engineers (IEEE), 2017-07-03) [Conference Paper]

Inter-relay interference (IRI) challenges the operation of two-path relaying systems. Furthermore, the unavailability of the channel state information (CSI) at the source and the limited detection capabilities at the relays prevent neither eliminating the interference nor adopting joint detection at the relays nodes. Improper signaling is a powerful signaling scheme that has the capability to reduce the interference impact at the receiver side and improves the achievable rate performance. Therefore, improper signaling is adopted at both relays, which have access to the global CSI. Then, improper signal characteristics are designed to maximize the total end-to-end achievable rate at the relays. To this end, both the power and the circularity coefficient, a measure of the impropriety degree of the signal, are optimized at the relays. Although the optimization problem is not convex, optimal power allocation for both relays for a fixed circularity coefficient is obtained. Moreover, the circularity coefficient is tuned to maximize the rate for a given power allocation. Finally, a joint solution of the optimization problem is proposed using a coordinate descent method based on alternate optimization. The simulation results show that employing improper signaling improves the achievable rate at medium and high IRI.

Full-duplex relaying under I/Q imbalance using improper Gaussian signaling

Javed, Sidrah; Amin, Osama; Alouini, Mohamed-Slim (2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2017-06-20) [Conference Paper]

In this paper, we study the benefits of employing improper Gaussian signaling (IGS) in full duplex relaying (FDR) suffering from in-phase and quadrature imbalance (IQI). Different from the traditional symmetric signaling scheme, proper Gaussian signaling (PGS), that is parametrized by its variance, IGS needs additional statistical-quantity called the pseudo-variance to be fully described. The cooperative system under consideration suffers from two types of interferences, the residual self-interference (RSI) and IQI. To evaluate the system performance gain using IGS, first we express the end-to-end achievable rate for different IQI. Then, we optimize the pseudo-variance to compensate the interferences impact and improve the end-to-end achievable rate. Interestingly, IGS-based scheme outperforms its counterpart PGS-based scheme, especially at higher interference-to-noise ratio. Our findings reveal that using single-user detection with asymmetric signaling can compensate both RSI and IQI and improve the system performance.

Networked traffic state estimation involving mixed fixed-mobile sensor data using Hamilton-Jacobi equations

Canepa, Edward S.; Claudel, Christian G. (Transportation Research Part B: Methodological, Elsevier BV, 2017-06-19) [Article]

Nowadays, traffic management has become a challenge for urban areas, which are covering larger geographic spaces and facing the generation of different kinds of traffic data. This article presents a robust traffic estimation framework for highways modeled by a system of Lighthill Whitham Richards equations that is able to assimilate different sensor data available. We first present an equivalent formulation of the problem using a Hamilton–Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton–Jacobi equation are linear ones. We then pose the problem of estimating the traffic density given incomplete and inaccurate traffic data as a Mixed Integer Program. We then extend the density estimation framework to highway networks with any available data constraint and modeling junctions. Finally, we present a travel estimation application for a small network using real traffic measurements obtained obtained during Mobile Century traffic experiment, and comparing the results with ground truth data.

Downlink resource allocation for multichannel TDMA visible light communications

Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Chaaban, Anas; Alouini, Mohamed-Slim (2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Institute of Electrical and Electronics Engineers (IEEE), 2017-05-12) [Conference Paper]

Optical wireless communications (OWC) in general and resource allocation in OWC networks particularly have gained lots of attention recently. In this work, we consider the resource allocation problem of a visible light communication downlink transmission system based on time division multiple access with the objective of maximizing spectral efficiency (SE). As for the operational conditions, we impose constraints on the average optical intensity, the energy consumption and the quality-of-service. To solve the non-convex problem, we transform the objective function into a difference of concave functions by solving a second order differential inequality. Then, we propose a low-complexity algorithm to solve the resource allocation problem. Finally, we show by simulations the SE performance gains achieved by optimizing the power allocation over equal power allocation in the considered system. Numerical results show the SE gains achieved by using this solution.

Impact of Improper Gaussian Signaling on the Achievable Rate of Overlay Cognitive Radio

Amin, Osama; Abediseid, Walid; Alouini, Mohamed-Slim (2017 IEEE Wireless Communications and Networking Conference (WCNC), Institute of Electrical and Electronics Engineers (IEEE), 2017-05-12) [Conference Paper]

Improper Gaussian signaling (IGS) has been recently shown to provide performance improvements in underlay cognitive radio systems as opposed to the conventional proper Gaussian signaling (PGS) scheme. For the first time, this paper implements IGS scheme in overlay cognitive radio system, where the secondary transmitter broadcasts a mixture of two different signals. The first signal is selected from the PGS scheme to support the primary message transmission. On the other hand, the second signal is chosen to be from the IGS scheme in order to reduce the interference effect on the primary receiver. We then optimally design the overlay cognitive radio that employs IGS to maximize the secondary link achievable rate while satisfying the minimum rate requirement of the primary network. In particular, we derive closed form expressions for the circularity coefficient used in the IGS scheme and the power distribution parameters. Simulation results are provided to support our theoretical derivations.

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