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Mohamed-Slim Alouini

Publications and source records attributed to Mohamed-Slim Alouini.

At least 379 records · Page 21Linked to original sources

Adaptive Acquisition Schemes for Photon-Limited Free-Space Optical Communications

Acquisition and tracking systems form an important component of free-space optical communications due to directional nature of the optical signal. Acquisition subsystems are needed in order to search and locate the receiver terminal in an uncertainty/search region with very narrow laser beams. In this paper, we have proposed and analyzed two adaptive search schemes for acquisition systems that perform better---for the low probability of detection---than the spiral scanning approach. The first of these schemes, the adaptive spiral search, provides a better acquisition time performance by dividing the search region into a number of smaller subregions, and prioritizing search in regions of higher probability mass. The second technique---the shotgun approach---searches the region in a random manner by sampling the search region according to a Gaussian distribution. The adaptive spiral scheme outperforms the shotgun approach in terms of acquisition time, especially if the number of search subregions is large enough. However, a higher pointing accuracy is required by the adaptive spiral search in order to search the region precisely. On the other hand, the shotgun scanning approach does not require such stringent pointing accuracy.

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Enhanced Huffman Coded OFDM with Index Modulation

In this paper, we propose an enhanced Huffman coded orthogonal frequency-division multiplexing with index modulation (EHC-OFDM-IM) scheme. The proposed scheme is capable of utilizing all legitimate subcarrier activation patterns (SAPs) and adapting the bijective mapping relation between SAPs and leaves on a given Huffman tree according to channel state information (CSI). As a result, a dynamic codebook update mechanism is obtained, which can provide more reliable transmissions. We take the average block error rate (BLER) as the performance evaluation metric and approximate it in closed form when the transmit power allocated to each subcarrier is independent of channel states. Also, we propose two CSI-based power allocation schemes with different requirements for computational complexity to further improve the error performance. Subsequently, we carry out numerical simulations to corroborate the error performance analysis and the proposed dynamic power allocation schemes. By studying the numerical results, we find that the depth of the Huffman tree has a significant impact on the error performance when the SAP-to-leaf mapping relation is optimized based on CSI. Meanwhile, through numerical results, we also discuss the trade-off between error performance and data transmission rate and investigate the impacts of imperfect CSI on the error performance of EHC-OFDM-IM.

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Signal Acquisition with Photon-Counting Detector Arrays in Free-Space Optical Communications

Pointing and acquisition are an important aspect of free-space optical communications because of the narrow beamwidth associated with the optical signal. In this paper, we have analyzed the pointing and acquisition problem in free-space optical communications for photon-counting detector arrays and Gaussian beams. In this regard, we have considered the maximum likelihood detection for detecting the location of the array, and analyzed the one-shot probabilities of missed detection and false alarm using the scaled Poisson approximation. Moreover, the upper/lower bounds on the probabilities of missed detection and false alarm for one complete scan are also derived, and these probabilities are compared with Monte Carlo approximations for a few cases. Additionally, the upper bounds on the acquisition time and the mean acquisition time are also derived. The upper bound on mean acquisition time is minimized numerically with respect to the beam radius for a constant signal-to-noise ratio scenario. Finally, the complementary distribution function of an upper bound on acquisition time is also calculated in a closed form. Our study concludes that an array of smaller detectors gives a better acquisition performance (in terms of acquisition time) as compared to one large detector of similar dimensions as the array.

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Compressive Sensing Based Channel Estimation for Millimeter-Wave Full-Dimensional MIMO with Lens-Array

Channel estimation (CE) for millimeter-wave (mmWave) lens-array suffers from prohibitive training overhead, whereas the state-of-the-art solutions require an extra complicated radio frequency phase shift network. By contrast, lens-array using antenna switching network (ASN) simplifies the hardware, but the associated CE is a challenging task due to the constraint imposed by ASN. This paper proposes a compressive sensing (CS)-based CE solution for full-dimensional (FD) lens-array, where the mmWave channel sparsity is exploited. Specifically, we first propose an approach of pilot training under the more severe haraware constraint imposed by ASN, and formulate the associated CE of lens-array as a CS problem. Then, a redundant dictionary is tailored for FD lens-array to combat the power leakage caused by the continuous angles of multipath components. Further, we design the baseband pilot signals to minimize the total mutual coherence of the measurement matrix based on CS theory for more reliable CE performance. Our solution provides a framework for applying CS techniques to lens-array using simple and practical ASN. Simulation results demonstrate the effectiveness of the proposed scheme.

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Analysis of 3D Localization in Underwater Optical Wireless Networks with Uncertain Anchor Positions

Localization accuracy is of paramount importance for the proper operation of underwater optical wireless sensor networks (UOWSNs). However, underwater localization is prone to hostile environmental impediments such as drifts due to the surface and deep currents. These cause uncertainty in the deployed anchor node positions and pose daunting challenges to achieve accurate location estimations. Therefore, this paper analyzes the performance of three-dimensional (3D) localization for UOWSNs and derive a closed-form expression for the Cramer Rao lower bound (CRLB) by using time of arrival (ToA) and angle of arrival (AoA) measurements under the presence of uncertainty in anchor node positions. Numerical results validate the analytical findings by comparing the localization accuracy in scenarios with and without anchor nodes position uncertainty. Results are also compared with the linear least square (LSS) method and weighted LLS (WLSS) method.

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A Survey of NOMA: Current Status and Open Research Challenges

Non-orthogonal multiple access (NOMA) has been considered as a study-item in 3GPP for 5G new radio (NR). However, it was decided not to continue with it as a work-item, and to leave it for possible use in beyond 5G. In this paper, we first review the discussions that ended in such decision. Particularly, we present simulation comparisons between the NOMA and multi-user multiple-input-multiple-output (MU-MIMO), where the possible gain of NOMA, compared to MU-MIMO, is negligible. Then, we propose a number of methods to reduce the implementation complexity and delay of both uplink (UL) and downlink (DL) NOMA-based transmission, as different ways to improve its efficiency. Here, particular attention is paid to reducing the receiver complexity, the cost of hybrid automatic repeat request as well as the user pairing complexity. As demonstrated, different smart techniques can be applied to improve the energy efficiency and the end-to-end transmission delay of NOMA-based systems.

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A UAV-Mounted Free Space Optical Communication: Trajectory Optimization for Flight Time

In this work, we address the trajectory optimization of a fixed-wing unmanned aerial vehicle (UAV) using free space optical communication (FSOC). Here, we focus on maximizing the flight time of the UAV by considering practical constraints for wireless UAV communication, including limited propulsion energy and required data rates. We find optimized trajectories in various atmospheric environments (e.g., moderate-fog and heavy-fog conditions), while also considering the channel characteristics of FSOC. In addition to maximizing the flight time, we consider the energy efficiency maximization and operation-time minimization problem to find the suboptimal solutions required to meet those constraints. Furthermore, we introduce a low-complexity approach to the proposed framework. In order to address the optimization problem, we conduct a bisection method and sequential programming and introduce a new feasibility check algorithm. Although our design considers suboptimal solutions owing to the nonconvexity of the problems, our simulations indicate that the proposed scheme exhibits a gain of approximately 44.12\% in terms of service time when compared to the conventional scheme.

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Prospect Theory for Human-Centric Communications

Entering the 5G/6G era, the core concept of human-centric communications has intensified the search effort into analytical frameworks for integrating technological and non-technological domains. Among non-technological domains, human behavioral, psychological, and socio-economic contexts are widely considered as indispensable elements for characterizing user experience (UE). In this study, we introduce the prospect theory as a promising methodology for modeling UE and perceptual measurements for human-centric communications. As the founding pillar of behavioral economics, the prospect theory proposes the non-linear quantity and probability perception of human psychology, which extends to five fundamental behavioral attributes that have profound implications for diverse disciplines. By expatiating on the prospect theoretic framework, we aim to provide a guideline for developing human-centric communications and articulate a novel interdisciplinary research area for further investigation.

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Intelligent Reflecting Surface Assisted Wireless Communication: Modeling and Channel Estimation

The recently completed 5G new radio standard is a result of several cutting-edge technologies, including massive multiple-input multiple-output (MIMO), millimeter (mm)-Wave communication and network densification. However, these technologies face two main practical limitations 1) the lack of control over the wireless channel, and 2) the high power consumption of the wireless interface. To address the need for green and sustainable future cellular networks, the concept of reconfiguring wireless propagation environments using Intelligent Reflecting Surfaces (IRS)s has emerged. An IRS comprises of a large number of low-cost passive antennas that can smartly reflect the impinging electromagnetic waves for performance enhancement. This paper looks at the evolution of the reflective radio concept towards IRSs, outlines the IRS-assisted multi-user multiple-input single-output (MISO) communication model and discusses how it differentiates from the conventional multi-antenna communication models. We propose a minimum mean squared error (MMSE) based channel estimation protocol for the design and analysis of IRS-assisted systems. Performance evaluation results at 2.5 GHz operating frequency are provided to illustrate the efficiency of the proposed system.

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LightFDG: An Integrated Approach to Flow Detection and Grooming in Optical Wireless DCNs

LightFDG is an integrated approach to flow detection (FD) and flow grooming (FG) in optical wireless data center networks (DCNs), which is interconnected via wavelength division multiplexing (WDM) based free-space optical (FSO) links. Since forwarding bandwidth-hungry elephant flows (EFs) and delay-sensitive mice flows (MFs) on the same path can cause severe performance degradation, the LightFDG optically grooms flows of each class into rack-to-rack (R2R) flows. Then, R2R-MF and R2R-EF flows are separately forwarded over lightpaths of separate MF and EF virtual topologies, respectively. Lightpaths are provisioned by jointly determining the capacity and route based on flows' arrival rate, size, and completion time request. To prevent EFs from congesting the MF lightpaths, high speed and accurate flow-detection mechanisms are also necessary for classifying EFs as soon as possible. Therefore, a fast-lightweight-and-accurate flow detection framework is developed by leveraging the transmission control protocol (TCP) behaviors. The proposed FD scheme has the flexibility of being implemented as in-network or centralized to classify flows of modifiable and unmodifiable hosts, respectively. Since the centralized scheme incurs considerable overhead, the processing and communication overhead is also mitigated by proposed techniques. Numerical results show that LightFDG outperforms traditional load balancers by about 3x for EFs and 10x for MFs. Along with the developed overhead mitigation methods, the centralized scheme is shown to provide up to 62x lower overhead with 100% accuracy and with about 224x higher detection speeds than the existing centralized solutions.

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Resource and Placement Optimization for Multiple UAVs using Backhaul Tethered Balloons

This paper studies the improvement of the achievable end-to-end data rate of ground users assisted with unmanned aerial vehicles (UAVs) and tethered balloons (TBs). The goal is to maximize the end-to-end throughput of a network suffering from the absence of terrestrial infrastructure. First, we solve an integer linear programming problem to optimize the associations. Then, we solve the UAVs transmit powers optimally by converting the problem into a convex one. Subsequently, an efficient algorithm is proposed to optimize the UAVs placement. Finally, our mathematical formalism is illustrated with some selected numerical results that show the advantages provided by our proposed scheme.

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Facilitating Satellite-Airborne-Terrestrial Integration for Dynamic and Infrastructure-less Networks

This paper studies the potential improvement in the achievable data rate available to ground users by integrating satellite, airborne, and terrestrial networks. The goal is to establish dynamic wireless services in remote or infrastructure-less areas. This integration uses high-altitude platforms in the exosphere, stratosphere, and troposphere for better altitude reuse coupled with emerging optical or other high-frequency directional transceivers. Hence they offer a significant increases in the scarce spectrum aggregate efficiency. However, managing resource allocation with deployment in this integrated system still has some difficulties. This paper aims to tackle resource management challenges by (i) providing wireless services to ground users in remote areas and connecting them with metropolitan and rural areas, (ii) employing high-altitude platforms (HAPs) equipped with free-space-optical communication modules for back-hauling backbone. Finally, we show how our results illustrate the advantages of using the proposed scheme.

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Improvement of the Global Connectivity using Integrated Satellite-Airborne-Terrestrial Networks with Resource Optimization

In this paper, we propose a novel wireless scheme that integrates satellite, airborne, and terrestrial networks aiming to support ground users. More specifically, we study the enhancement of the achievable users' throughput assisted with terrestrial base stations, high altitude platforms (HAPs), and satellite station. The goal is to optimize the resource allocations and the HAPs locations in order to maximize the users' throughput. In this context, we propose to solve the optimization problem in two stages; first a short-term stage and then a long-term stage. In the short-term stage, we start by proposing a near optimal solution and low complexity solution to solve the associations and power allocations. In the first solution, we formulate and solve a binary linear optimization problem to find the best associations and then using Taylor expansion approximation to optimally determine the power allocations. While in the second solution, we propose a low complexity approach based on frequency partitioning technique to solve the associations and power allocations. One the other hand, in the long-term stage, we optimize the locations of the HAPs by proposing an efficient algorithm based on a recursive shrink-and-realign process. Finally, selected numerical results show the advantages provided by our proposed optimization scheme.

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Asymptotic Max-Min SINR Analysis of Reconfigurable Intelligent Surface Assisted MISO Systems

This work focuses on the downlink of a single-cell multi-user system in which a base station (BS) equipped with $M$ antennas communicates with $K$ single-antenna users through a reconfigurable intelligent surface (RIS) installed in the line-of-sight (LoS) of the BS. RIS is envisioned to offer unprecedented spectral efficiency gains by utilizing $N$ passive reflecting elements that induce phase shifts on the impinging electromagnetic waves to smartly reconfigure the signal propagation environment. We study the minimum signal-to-interference-plus-noise ratio (SINR) achieved by the optimal linear precoder (OLP), that maximizes the minimum SINR subject to a given power constraint for any given RIS phase matrix, for the cases where the LoS channel matrix between the BS and the RIS is of rank-one and of full-rank. In the former scenario, the minimum SINR achieved by the RIS-assisted link is bounded by a quantity that goes to zero with $K$. For the high-rank scenario, we develop accurate deterministic approximations for the parameters of the asymptotically OLP, which are then utilized to optimize the RIS phase matrix. Simulation results show that RISs can outperform half-duplex relays with a small number of passive reflecting elements while large RISs are needed to outperform full-duplex relays.

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A PHY Layer Security Analysis of Uplink Cooperative Jamming-Based Underlay CRNs with Multi-Eavesdroppers

In this paper, the physical layer security of a dual-hop underlay uplink cognitive radio network is investigated over Nakagami-m fading channels. Specifically, multiple secondary sources are taking turns in accessing the licensed spectrum of the primary users and communicating with a multiantenna secondary base station D through the aid of a multiantenna relay R in the presence of M eavesdroppers that are also equipped with multiple antennas. Among the remaining nodes, one jammer is randomly selected to transmit an artificial noise to disrupt all the eavesdroppers that are attempting to intercept the communication of the legitimate links i.e., S-R and R-D. The received signals at each node are combined using maximal-ratio combining. Secrecy analysis is provided by deriving closed-form and asymptotic expressions for the secrecy outage probability. The impact of several key parameters on the system's secrecy e.g., transmit power of the sources, number of eavesdroppers, maximum tolerated interference power, and the number of diversity branches is investigated. Importantly, by considering two scenarios, namely (i) absence and (ii) presence of a friendly jammer, new insights are obtained for the considered communication system. Especially, we tend to answer to the following question: Can better secrecy be achieved without jamming by considering a single antenna at eavesdroppers and multiple-ones at the legitimate users (i.e., relay and end-user) rather than sending permanently an artificial noise and considering that both the relay and the destination are equipped with a single antenna, while multiple antennas are used by the eavesdroppers? The obtained results are corroborated through Monte Carlo simulation and show that the system's security can be enhanced by adjusting the aforementioned parameters.

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Stochastic Geometry Analysis of Hybrid Aerial Terrestrial Networks with mmWave Backhauling

To meet increasing data demands, service providers are considering the use of Unmanned aerial vehicles (UAVs) for delivering connectivity as aerial base stations (BSs). UAVs are especially important to provide connectivity in case of disasters and accidents which may cripple completely the existing terrestrial networks. However, in order to maintain the communication of UAVs with the core network, it is essential to provide them with wireless backhaul connection to terrestrial BSs. In this work, we use stochastic geometry to study the impact of millimeter-wave (mmWave) backhauling of UAVs in a hybrid aerial-terrestrial cellular network where the UAVs are added to assist terrestrial BSs in delivering reliable service to users (UEs). In the proposed model, the UE can associate to either a terrestrial BS or a UAV connected to a BS to get backhaul support. The performance of the proposed model is evaluated in terms of coverage probability and validated against intensive simulations. The obtained results unveil that the quality of the UAVs' mmWave backhaul link has a significant impact on the UE 's experience and the deployment of UAVs must be adjusted accordingly.

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A Unified Statistical Model for Atmospheric Turbulence-Induced Fading in Orbital Angular Momentum Multiplexed FSO Systems

This paper proposes a unified statistical channel model to characterize the atmospheric turbulence induced distortions faced by orbital angular momentum (OAM) in free space optical (FSO) communication systems. In this channel model, the self-channel irradiance of OAM modes as well as crosstalk irradiances between different OAM modes are characterized by a Generalized Gamma distribution (GGD). The latter distribution is shown to provide an excellent match with simulated data for all regimes of atmospheric turbulence. Therefore, it can be used to overcome the computationally complex numerical simulations to model the propagation of OAM modes through atmospheric turbulent FSO channels. The GGD allows obtaining very simple tractable closed-form expressions for a variety of performance metrics. Indeed, the average capacity, the bit-error rate, and the outage probability are derived for FSO systems using single OAM mode transmission with direct detection. Furthermore, we extend our study to FSO systems using OAM mode diversity to improve the performance. By using a maximum ratio combining (MRC) at the receiver, the GGD is also shown to fit the simulated combined received optical powers. Finally, space-time (ST) coding is proposed to provide diversity and multiplexing gains, and the error probability is theoretically derived under the newly proposed generic model.

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Frequency Diverse Array Radar: New Results and Discrete Fourier Transform Based Beampattern

In the phased-array radar (PAR) signals from each antenna are transmitted at the same carrier frequency, which yields narrowly focused only angle dependent beampattern. In contrast, in the frequency-diverse-array (FDA) radar signals from antenna array are generally transmitted at linearly increasing frequencies that yields range, time, and angle dependent beampattern. Reported literature on FDA radar missed the contribution of path-differences in the signal model due to the antenna array elements, which may lead to misleading results. In this work, incorporating missed path-differences, the signal model of FDA radar is corrected. Using the corrected signal model, it is shown that the instantaneous beampattern depends on the number of transmit antenna and average beampattern depends on the product of frequency-offset and pulse-duration. Moreover, to illuminate the desired region-of-interest for longer dwell time, discrete-Fourier-transform based low-complexity algorithm is proposed. In contrast to the conventional FDA radar's 'S' shaped beampattern, the beampattern of the proposed algorithm changes linearly with range. Simulation results compare the performance of our proposed algorithm with the existing ones and show the superiority of our proposed algorithm.

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