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Author

Alouini, Mohamed-Slim (7)

Kammoun, Abla (3)Rached, Nadhir B. (2)Tempone, Raul (2)Al-Naffouri, Tareq Y. (1)View MoreDepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (7)
Electrical Engineering Program (7)

Applied Mathematics and Computational Science Program (2)Center for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ) (1)EE program, King Abdullah University of Science and Technology, Thuwal, Mekkah Province, Saudi Arabia (1)View MoreJournal
IEEE Transactions on Communications (7)

PublisherInstitute of Electrical and Electronics Engineers (IEEE) (7)Subjectoutage probability (3)importance sampling (2)active antenna system (AAS) (1)asymmetric complex signaling (1)bounded relative error (1)View MoreTypeArticle (7)Year (Issue Date)
2017 (7)

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Open Access (7)

Now showing items 1-7 of 7

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Wireless Energy Harvesting Using Signals from Multiple Fading Channels

Chen, Yunfei; Zhao, Nan; Alouini, Mohamed-Slim (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-08-01) [Article]

In this paper, we study the average, the probability density function and the cumulative distribution function of the harvested power. In the study, the signals are transmitted from multiple sources. The channels are assumed to be either Rician fading or Gamma-shadowed Rician fading. The received signals are then harvested by using either a single harvester for simultaneous transmissions or multiple harvesters for transmissions at different frequencies, antennas or time slots. Both linear and nonlinear models for the energy harvester at the receiver are examined. Numerical results are presented to show that, when a large amount of harvested power is required, a single harvester or the linear range of a practical nonlinear harvester are more efficient, to avoid power outage. Further, the power transfer strategy can be optimized for fixed total power. Specifically, for Rayleigh fading, the optimal strategy is to put the total power at the source with the best channel condition and switch off all other sources, while for general Rician fading, the optimum magnitudes and phases of the transmitting waveforms depend on the channel parameters.

Full-Duplex Relaying with Improper Gaussian Signaling over Nakagami-m Fading Channels

Gaafar, Mohamed; Khafagy, Mohammad Galal; Amin, Osama; Schaefer, Rafael F.; Alouini, Mohamed-Slim (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-10-04) [Article]

We study the potential employment of improper Gaussian signaling (IGS) in full-duplex relaying (FDR) with non-negligible residual self-interference (RSI) under Nakagami- m fading. IGS is recently shown to outperform traditional proper Gaussian signaling (PGS) in several interference-limited settings. In this work, IGS is employed as an attempt to alleviate RSI. We use two performance metrics, namely, the outage probability and the ergodic rate. First, we provide upper and lower bounds for the system performance in terms of the relay transmit power and circularity coefficient, a measure of the signal impropriety. Then, we numerically optimize the relay signal parameters based only on the channel statistics to improve the system performance. Based on the analysis, IGS allows FDR to operate even with high RSI. The results show that IGS can leverage higher power budgets to enhance the performance, meanwhile it relieves RSI impact via tuning the signal impropriety. Interestingly, one-dimensional optimization of the circularity coefficient, with maximum relay power, offers a similar performance as the joint optimization, which reduces the optimization complexity. From a throughput standpoint, it is shown that IGS-FDR can outperform not only PGS-FDR, but also half-duplex relaying with/without maximum ratio combining over certain regions of the target source rate.

On the Efficient Simulation of the Distribution of the Sum of Gamma-Gamma Variates with Application to the Outage Probability Evaluation Over Fading Channels

Ben Issaid, Chaouki; Rached, Nadhir B.; Kammoun, Abla; Alouini, Mohamed-Slim; Tempone, Raul (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-01-26) [Article]

The Gamma-Gamma distribution has recently emerged in a number of applications ranging from modeling scattering and reverberation in sonar and radar systems to modeling atmospheric turbulence in wireless optical channels. In this respect, assessing the outage probability achieved by some diversity techniques over this kind of channels is of major practical importance. In many circumstances, this is related to the difficult question of analyzing the statistics of a sum of Gamma- Gamma random variables. Answering this question is not a simple matter. This is essentially because outage probabilities encountered in practice are often very small, and hence the use of classical Monte Carlo methods is not a reasonable choice. This lies behind the main motivation of the present work. In particular, this paper proposes a new approach to estimate the left tail of the sum of Gamma-Gamma variates. More specifically, we propose robust importance sampling schemes that efficiently evaluates the outage probability of diversity receivers over Gamma-Gamma fading channels. The proposed estimators satisfy the well-known bounded relative error criterion for both maximum ratio combining and equal gain combining cases. We show the accuracy and the efficiency of our approach compared to naive Monte Carlo via some selected numerical simulations.

On the Efficient Simulation of Outage Probability in a Log-normal Fading Environment

Rached, Nadhir B.; Kammoun, Abla; Alouini, Mohamed-Slim; Tempone, Raul (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-02-15) [Article]

The outage probability (OP) of the signal-to-interference-plus-noise ratio (SINR) is an important metric that is used to evaluate the performance of wireless systems. One difficulty toward assessing the OP is that, in realistic scenarios, closed-form expressions cannot be derived. This is for instance the case of the Log-normal environment, in which evaluating the OP of the SINR amounts to computing the probability that a sum of correlated Log-normal variates exceeds a given threshold. Since such a probability does not admit a closed-form expression, it has thus far been evaluated by several approximation techniques, the accuracies of which are not guaranteed in the region of small OPs. For these regions, simulation techniques based on variance reduction algorithms is a good alternative, being quick and highly accurate for estimating rare event probabilities. This constitutes the major motivation behind our work. More specifically, we propose a generalized hybrid importance sampling scheme, based on a combination of a mean shifting and a covariance matrix scaling, to evaluate the OP of the SINR in a Log-normal environment. We further our analysis by providing a detailed study of two particular cases. Finally, the performance of these techniques is performed both theoretically and through various simulation results.

Design of 5G Full Dimension Massive MIMO Systems

Nadeem, Qurrat-Ul-Ain; Kammoun, Abla; Debbah, Merouane; Alouini, Mohamed-Slim (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-10-13) [Article]

This work discusses full-dimension multiple-inputmultiple- output (FD-MIMO) technology, which is currently an active area of research and standardization in wireless communications for evolution towards Fifth Generation (5G) cellular systems. FD-MIMO utilizes an active antenna system (AAS) with a two-dimensional (2D) planar array structure, that not only allows a large number of antenna elements to be packed within feasible base station form factors but also provides the ability of adaptive electronic beamforming in the threedimensional (3D) space. However, the compact structure of largescale planar arrays drastically increases the spatial correlation in FD-MIMO systems. In order to account for its effects, the generalized spatial correlation functions for channels constituted by individual elements and overall antenna ports in the AAS are derived. Exploiting the quasi-static channel covariance matrices of users, the problem of determining the optimal downtilt weight vector for antenna ports, which maximizes the minimum signalto- interference ratio of a multi-user multiple-input-single-output system, is formulated as a fractional optimization problem. A quasi-optimal solution is obtained through the application of semi-definite relaxation and Dinkelbach’s method. Finally, the user-group specific elevation beamforming scenario is devised, which offers significant performance gains as confirmed through simulations. These results have direct application in the analysis of 5G FD-MIMO systems.

Distributed Hybrid Scheduling in Multi-Cloud Networks using Conflict Graphs

Douik, Ahmed S.; Dahrouj, Hayssam; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-09-07) [Article]

Recent studies on cloud-radio access networks assume either signal-level or scheduling-level coordination. This paper considers a hybrid coordinated scheme as a means to benefit from both policies. Consider the downlink of a multi-cloud radio access network, where each cloud is connected to several base-stations (BSs) via high capacity links, and, therefore, allows for joint signal processing within the cloud transmission. Across the multiple clouds, however, only scheduling-level coordination is permitted, as low levels of backhaul communication are feasible. The frame structure of every BS is composed of various time/frequency blocks, called power-zones (PZs), which are maintained at a fixed power level. The paper addresses the problem of maximizing a network-wide utility by associating users to clouds and scheduling them to the PZs, under the practical constraints that each user is scheduled to a single cloud at most, but possibly to many BSs within the cloud, and can 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 considered scheduling problem is, then, shown to be equivalent to a maximum-weight independent set problem in the constructed graph, which can be solved using efficient techniques. The paper then proposes solving the problem using both optimal and heuristic algorithms that can be implemented in a distributed fashion across the network. The proposed distributed algorithms rely on the well-chosen structure of the constructed conflict graph utilized to solve the maximum-weight independent set problem. Simulation results suggest that the proposed optimal and heuristic hybrid scheduling strategies provide appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

Gharbieh, Mohammad; Elsawy, Hesham; Bader, Ahmed; Alouini, Mohamed-Slim (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-05-02) [Article]

The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

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