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Mohamed-Slim Alouini

Publications and source records attributed to Mohamed-Slim Alouini.

At least 217 records · Page 12Linked to original sources

Dedicating Cellular Infrastructure for Aerial Users: Advantages and Potential Impact on Ground Users

A new generation of aerial vehicles is hopeful to be the next frontier for the transportation of people and goods, becoming even as important as ground users in the communication systems. To enhance the coverage of aerial users, appropriate adjustments should be made to the existing cellular networks that mainly provide services for ground users by the down-tilted antennas of the terrestrial base stations (BSs). It is promising to up-tilt the antennas of a subset of BSs for serving aerial users through the mainlobe. With this motivation, in this work, we use tools from stochastic geometry to analyze the coverage performance of the adjusted cellular network (consisting of the up-tilted BSs and the down-tilted BSs). Correspondingly, we present exact and approximate expressions of the signal-to-interference ratio (SIR)-based coverage probabilities for users in the sky and on the ground, respectively. Numerical results verify the analysis accuracy and clarify the advantages of up-tilting BS antennas on the communication connectivity of aerial users without the potential adverse impact on the quality of service (QoS) of ground users.

cs.IT↗

Joint Communication and Computation in Hybrid Cloud/Mobile Edge Computing Networks

Facing a vast amount of connections, huge performance demands, and the need for reliable connectivity, the sixth generation of communication networks (6G) is envisioned to implement disruptive technologies that jointly spur connectivity, performance, and reliability. In this context, this paper proposes, and evaluates the benefit of, a hybrid central cloud (CC) computing and mobile edge computing (MEC) platform, especially introduced to balance the network resources required for joint computation and communication. Consider a hybrid cloud and MEC system, where several power-hungry multi-antenna unmanned aerial vehicles (UAVs) are deployed at the cell-edge to boost the CC connectivity and relieve part of its computation burden. While the multi-antenna base stations are connected to the cloud via capacity-limited fronthaul links, the UAVs serve the cell-edge users with limited power and computational capabilities. The paper then considers the problem of maximizing the weighted network sum-rate subject to per-user delay, computational capacity, and power constraints, so as to determine the beamforming vectors and computation allocations. Such intricate non-convex optimization problem is tackled using an iterative algorithm that relies on $\ell_0$-norm relaxation, successive convex approximation, and fractional programming, and has the compelling ability to be implemented in a distributed fashion across the multiple UAVs and the CC. The paper results illustrate the numerical prospects of the proposed algorithm for enabling joint communication and computation, and highlight the appreciable improvements of data processing delays and throughputs as compared to conventional system strategies.

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Sharp Analysis of RLS-based Digital Precoder with Limited PAPR in Massive MIMO

This paper focuses on the performance analysis of a class of limited peak-to-average power ratio (PAPR) precoders for downlink multi-user massive multiple-input multiple-output (MIMO) systems. Contrary to conventional precoding approaches based on simple linear precoders such as maximum ratio transmission (MRT) and regularized zero-forcing (RZF), the precoders in this paper are obtained by solving a convex optimization problem. To be specific, these precoders are designed so that the power of each precoded symbol entry is restricted, and the PAPR at each antenna is tunable. By using the Convex Gaussian Min-max Theorem (CGMT), we analytically characterize the empirical distribution of the precoded vector and the joint empirical distribution between the distortion and the intended symbol vector. This allows us to study the performance of these precoders in terms of per-antenna power, per-user distortion power, signal-to-noise and distortion ratio (SINAD), and bit error probability. We show that for this class of precoders, there is an optimal transmit per-antenna power that maximizes the system performance in terms of SINAD and bit error probability.

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How Much Exposure from 5G Towers is Radiated over Children, Teenagers, Schools and Hospitals?

The rolling-out of 5G antennas over the territory is a fundamental step to provide 5G connectivity. However, little efforts have been done so far on the exposure assessment from 5G cellular towers over young people and "sensitive" buildings, like schools and medical centers. To face such issues, we provide a sound methodology for the numerical evaluation of 5G (and pre-5G) downlink exposure over children, teenagers, schools and medical centers. We then apply the proposed methodology over two real scenarios. Results reveal that the exposure from 5G cellular towers will increase in the forthcoming years, in parallel with the growth of the 5G adoption levels. However, the exposure levels are well below the maximum ones defined by international regulations. Moreover, the exposure over children and teenagers is similar to the one of the whole population, while the exposure over schools and medical centers can be lower than the one of the whole set of buildings. Finally, the exposure from 5G is strongly lower than the pre-5G one when the building attenuation is introduced and a maturity adoption level for 5G is assumed.

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

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 $\frac{1}{4\ln2}$ bits/J, while HARQ-CC and HARQ-IR can achieve the same maximal energy efficiency as $\frac{κ_\infty}{4\ln2}$ bits/J where $κ_\infty = 1.6617$. 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.

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Maritime Communications: A Survey on Enabling Technologies, Opportunities, and Challenges

Water covers 71% of the Earth's surface, where the steady increase in oceanic activities has promoted the need for reliable maritime communication technologies. The existing maritime communication systems involve terrestrial, aerial, and satellite networks. This paper presents a holistic overview of the different forms of maritime communications and provides the latest advances in various marine technologies. The paper first introduces the different techniques used for maritime communications over the RF and optical bands. Then, we present the channel models for RF and optical bands, modulation and coding schemes, coverage and capacity, and radio resource management in maritime communications. After that, the paper presents some emerging use cases of maritime networks, such as the Internet of Ships (IoS) and the ship-to-underwater Internet of things (IoT). Finally, we highlight a few exciting open challenges and identify a set of future research directions for maritime communication, including bringing broadband connectivity to the deep sea, using THz and visible light signals for on-board applications, and data-driven modeling for radio and optical marine propagation.

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Stochastic Geometry-based Analysis of Multi-Purpose UAVs for Package and Data Delivery

Using drones for communications and transportation is drawing great attention in many practical scenarios, such as package delivery and providing additional wireless coverage. However, the increasing demand for UAVs from industry and academia will cause aerial traffic conflicts in the future. This, in turn, motivates the idea of this paper: multi-purpose UAVs, acting as aerial wireless data relays and means of aerial transportation simultaneously, to deliver packages and data at the same time. This paper aims to analyze the feasibility of using drones to collect and deliver data from the Internet of Things (IoT) devices to terrestrial base stations (TBSs) while delivering packages from warehouses to residential areas. We propose an algorithm to optimize the trajectory of UAVs to maximize the size of collected/delivered data while minimizing the total round trip time subject to the limited onboard battery of UAVs. Specifically, we use tools from stochastic geometry to model the locations of the IoT clusters and the TBSs and study the system performance with respect to energy efficiency, average size of collected/delivered data, and package delivery time. Our numerical results reveal that multi-functional UAVs have great potential to enhance the efficiency of both communication and transportation networks.

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Technical Report: Development of an Ultrahigh Bandwidth Software-defined Radio Platform

For the development of new digital signal processing systems and services, the rapid, easy, and convenient prototyping of ideas and the rapid time-to-market of products are becoming important with advances in technology. Conventionally, for the development stage, particularly when confirming the feasibility or performance of a new system or service, an idea is first confirmed through a computerbased software simulation after developing an accurate model of the operating environment. Next, this idea is validated and tested in the real operating environment. The new systems or services and their operating environments are becoming increasingly complicated. Hence, their development processes too are more complex cost- and time-intensive tasks that require engineers with skill and professional knowledge/experience. Furthermore, for ensuring fast time-to-market, all the development processes encompassing the (i) algorithm development, (ii) product prototyping, and (iii) final product development, must be closely linked such that they can be quickly completed. In this context, the aim of this paper is to propose an ultrahigh bandwidth software-defined radio platform that can prototype a quasi-real-time operating system without a developer having sophisticated hardware/software expertise. This platform allows the realization of a software-implemented digital signal processing system in minimal time with minimal efforts and without the need of a host computer.

cs.IT↗

Laser-Powered UAVs for Wireless Communication Coverage: A Large-Scale Deployment Strategy

The use of unmanned aerial vehicles (UAVs) is strongly advocated for sixth-generation (6G) networks, as the 6G standard will not be limited to improving broadband services, but will also target the extension of the geographical cellular coverage. In this context, the deployment of UAVs is considered a key solution for seamless connectivity and reliable coverage. That being said, it is important to underline that although UAVs are characterized by their high mobility and their ability to establish line-of-sight (LOS) links, their use is still impeded by several factors such as weather conditions, their limited computing power, and, most importantly, their limited energy. In this work, we are aiming for the novel technology that enables indefinite wireless power transfer for UAVs using laser beams. We propose a novel UAV deployment strategy, based on which we analyze the overall performance of the system in terms of wireless coverage. To this end, we use tractable tools from stochastic geometry to model the complex communication system. We analyze the user's connectivity profile under different laser charging capabilities and in different type of environments. We show a decrease in the coverage probability by more than 12% in moderate-to-strong turbulence conditions compared to low turbulence conditions. We also show how the connection rate to the aerial network significantly decreases in favor of the terrestrial network for short laser charging ranges. We conclude that laser-powered drones are considered interesting alternatives when placed in LOS with users, in low-to-moderate optical turbulence, and at reasonable ranges from the charging stations.

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Performance Analysis of Charging Infrastructure Sharing in UAV and EV-involved Networks

Electric vehicles (EVs) and unmanned aerial vehicles (UAVs) show great potential in modern transportation and communication networks, respectively. However, with growing demands for such technologies, the limited energy infrastructure becomes the bottleneck for their future growth. It might be of high cost and low energy efficiency for all the operators to each have their own dedicated energy infrastructure, such as charging stations. In this paper, we analyze a wireless charging infrastructure sharing strategy in UAV and EV-involved networks. We consider a scenario where UAVs can charge in EV charging stations and pay for the sharing fee. On the EVs' side, sharing infrastructure can earn extra profit but their service quality, such as waiting time, might slightly reduce. On the UAVs' side, if renting EV charging stations can achieve an acceptable system performance, say high coverage probability, while considering the cost, they may not need to build their dedicated charging stations. In this case, we use tools from stochastic geometry to model the locations and propose an optimization problem that captures the aforementioned trade-offs between cost or profit and quality of service. Our numerical results show that sharing infrastructure slightly increases the waiting time of EVs, say within $5$ min, but dramatically decreases the waiting time of drones, say more than $50$ min, and deploying more charging stations do achieve better performances, but all these better performances are expected to cost more.

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Energy Efficiency Analysis of Charging Pads-powered UAV-enabled Wireless Networks

This paper analyzes the energy efficiency of a novel system model where unmanned aerial vehicles (UAVs) are used to provide coverage for user hotspots (user clusters) and are deployed on charging pads to enhance the flight time. We introduce a new notion of "cluster pairs" to capture the dynamic nature of the users' spatial distribution in order to exploit one of the top advantages of UAVs, which is the mobility and relocation flexibility. Using tools from stochastic geometry, we first derive a new distance distribution that is vital for energy efficiency analysis. Next, we compute the coverage probability under two deployment strategies: (i) one UAV per cluster pair, and (ii) one UAV per cluster. Finally, we compute the energy efficiency for both strategies. Our numerical results reveal which of the two strategies is better for different system parameters. Our work investigates some new aspects of the UAV-enabled communication system such as the dynamic density of users and the advantages or disadvantages of one- or two-UAV deployment strategies per cluster pair. By considering the relationships between the densities of user cluster pairs and the charging pads, it is shown that an optimal cluster pair density exists to maximize energy efficiency.

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Conditional Contact Angle Distribution in LEO Satellite-Relayed Transmission

This letter characterizes the contact angle distribution based on the condition that the relay low earth orbit (LEO) satellite is in the communication range of both the ground transmitter and the ground receiver. As one of the core distributions in stochastic geometry-based routing analysis, the analytical expression of the \ac{CDF} of the conditional contact angle is derived. Furthermore, the conditional contact angle is applied to analyze the inaccessibility of common satellites between the ground transmitter and receiver. Finally, with the help of the conditional contact angle, coverage probability and achievable data rate in LEO satellite-relayed transmission are studied.

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Max-Min Data Rate Optimization for RIS-aided Uplink Communications with Green Constraints

Smart radio environments aided by reconfigurable intelligent reflecting surfaces (RIS) have attracted much research attention recently. We propose a joint optimization strategy for beamforming, RIS phases, and power allocation to maximize the minimum SINR of an uplink RIS-aided communication system. The users are subject to constraints on their transmit power. We derive a closed-form expression for the beam forming vectors and a geometric programming-based solution for power allocation. We also propose two solutions for optimizing the phase shifts at the RIS, one based on the matrix lifting method and one using an approximation for the minimum function. We also propose a heuristic algorithm for optimizing quantized phase shift values. The proposed algorithms are of practical interest for systems with constraints on the maximum allowable electromagnetic field exposure. For instance, considering $24$-element RIS, $12$-antenna BS, and $6$ users, numerical results show that the proposed algorithm achieves close to $300 \%$ gain in terms of minimum SINR compared to a scheme with random RIS phases.

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Evaluating the Accuracy of Stochastic Geometry Based Models for LEO Satellite Networks Analysis

This paper investigates the accuracy of recently proposed stochastic geometry-based modeling of low earth orbit (LEO) satellite networks. In particular, we use the Wasserstein Distance-inspired method to analyze the distances between different models, including Fibonacci lattice and orbit models. We propose an algorithm to calculate the distance between the generated point sets. Next, we test the algorithm's performance and analyze the distance between the stochastic geometry model and other more widely acceptable models using numerical results.

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Post-Disaster Communications: Enabling Technologies, Architectures, and Open Challenges

The number of disasters has increased over the past decade where these calamities significantly affect the functionality of communication networks. In the context of 6G, airborne and spaceborne networks offer hope in disaster recovery to serve the underserved and to be resilient in calamities. Therefore, this paper surveys the state-of-the-art literature on post-disaster wireless communication networks and provides insights for the future establishment of such networks. In particular, we first give an overview of the works investigating the general procedures and strategies for counteracting any large-scale disasters. Then, we present the possible technological solutions for post-disaster communications, such as the recovery of the terrestrial infrastructure, installing aerial networks, and using spaceborne networks. Afterward, we shed light on the technological aspects of post-disaster networks, primarily the physical and networking issues. We present the literature on channel modeling, coverage and capacity, radio resource management, localization, and energy efficiency in the physical layer and discuss the integrated space-air-ground architectures, routing, delay-tolerant/software-defined networks, and edge computing in the networking layer. This paper also presents interesting simulation results which can provide practical guidelines about the deployment of ad hoc network architectures in emergency scenarios. Finally, we present several promising research directions, namely backhauling, placement optimization of aerial base stations, and the mobility-related aspects that come into play when deploying aerial networks, such as planning their trajectories and the consequent handovers.

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Effect of Strong Time-Varying Transmission Distance on LEO Satellite-Terrestrial Deliveries

In this paper, we investigate the effect of the strong time-varying transmission distance on the performance of the low-earth orbit (LEO) satellite-terrestrial transmission (STT) system. We propose a new analytical framework using finite-state Markov channel (FSMC) model and time discretization method. Moreover, to demonstrate the applications of the proposed framework, the performances of two adaptive transmissions, rate-adaptive transmission (RAT) and power-adaptive transmission (PAT) schemes, are evaluated for the cases when the transmit power or the transmission rate at the LEO satellite is fixed. Closed-form expressions for the throughput, energy efficiency (EE), and delay outage rate (DOR) of the considered systems are derived and verified, which are capable of addressing the capacity, energy efficiency, and outage rate performance of the considered LEO STT scenarios with the proposed analytical framework.

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Toward Sustainable Transportation: Accelerating Vehicle Electrification with Dynamic Charging Deployment

Electric vehicles (EVs) are being actively adopted as a solution to sustainable transportation. However, a bottleneck remains with charging, where two of the main problems are the long charging time and the range anxiety of EV drivers. In this research, we investigate the deployment of dynamic charging systems, i.e., electrified roads that wirelessly charge EVs on the go, with a view to accelerating EVs adoption rate. We propose a traffic-based deployment strategy, statistically quantify its impact, and apply the strategy to two case studies of real traffic in New York City (USA) and Xi'an (China). We find that our analytical estimates not only closely match the real data, but they also suggest that dynamic charging considerably extends the driving range of popular EV models in urban mobility. For example, when only 5% of the existing roads in New York City are equipped with this technology, an EV model such as the Nissan Leaf will approximately maintain its battery level without stopping to recharge. If the percentage of charging roads is increased to 10%, then the Leaf will gain nearly 10% of its battery after every 40 kilometers of driving. Our framework provides a solution to public and private organizations that support and facilitate vehicle electrification through charging infrastructure.

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On the Performance Optimization of Two-way Hybrid VLC/RF based IoT System over Cellular Spectrum

This paper investigates the system outage performance of a useful architecture of two-way hybrid visible light communication/radio frequency (VLC/RF) communication using overlay mode of cooperative cognitive radio network (CCRN). The demand of high data rate application can be fulfilled using VLC link and communication over a wide area of coverage with high reliability can be achieved through RF link. In the proposed architecture, cooperative communication between two licensed user (LU) nodes is accomplished via an aggregation agent (AA). AA can perform like a relay node and in return, it can access the LU spectrum for two-way communications with Internet-of-Things (IoT) device. First, closed form expressions of outage probability of both LU and IoT communication are established. On the basis of these expressions, optimization problems are formulated to achieve minimum outage probability of both LU and IoT network. The impacts of both VLC and RF system parameters on these systems outage probability and throughput are finally shown in simulation results.

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