arXiv subjects

Chadi Assi

Publications and source records attributed to Chadi Assi.

At least 73 records · Page 4Linked to original sources

arXiv2022

Optimizing Information Freshness in RIS-assisted NOMA-based IoT Networks

This paper investigates the benefits of integrating reconfigurable intelligent surface (RIS) on minimizing the average sum age of information (AoI) in uplink non-orthogonal multiple access-based Internet-of-Things (IoT) networks. In this setup, an optimization problem is formulated to optimize the RIS configuration, the transmit power per IoT device and the clustering policy of IoT devices. The formulated problem is a mixed-integer non-convex one, and in order to solve it we obtain first the RIS configuration by adopting a semi-definite relaxation (SDR) approach. Afterwards, the joint power allocation and user-clustering problem is solved using the concept of bi-level optimization and is decomposed into an outer user clustering problem and an inner power allocation problem. Optimal closed-form expressions are derived for the inner problem and the Hungarian method is employed to solve the outer one. Numerical results demonstrate the performance superiority of our approach.

cs.IT↗

arXiv2021

Electric Vehicle Attack Impact on Power Grid Operation

The increasing need for reducing greenhouse gas emissions and the drive for green cities have promoted the use of electric vehicles due to their environmental benefits. In fact, countries have set their own targets and are offering incentives for people to purchase EVs as opposed to traditional gasoline-powered cars. Manufacturers have been hastily deploying charging stations to meet the charging requirements of the EVs on the road. This rapid deployment has contributed to the EV ecosystem's lack of proper security measures, raising multiple questions related to the power grid security and vulnerability. In this paper, we offer a complete examination of the EV ecosystem from the vulnerability to the attacks and finally the solutions. We start by examining the existing vulnerabilities in the EV ecosystem that can be exploited to control the EV charging and launch attacks against the power grid. We then discuss the non-linear nature of the EV charging load and simulate multiple attacks that can be launched against the power grid using these EVs. EV loads have high reactive power demand which can have a larger impact on the grid compared to residential loads. We perform simulations on two power grids and demonstrate that while the grid can recover after a 48 MW attack utilizing traditional residential loads, a smaller 30 MW EV load attack can completely destabilize the system. Finally, we suggest several patches for the existing vulnerabilities and discuss two methods aimed at detecting EV attacks.

eess.SY↗

arXiv2021

RIS-Assisted UAV for Timely Data Collection in IoT Networks

Intelligent Transportation Systems are thriving thanks to a wide range of technological advances, namely 5G communications, Internet of Things, artificial intelligence and edge computing. Central to this is the wide deployment of smart sensing devices and accordingly the large amount of harvested information to be processed for timely decision making. Robust network access is, hence, essential for offloading the collected data before a set deadline, beyond which the data loses its value. In environments where direct communication can be impaired by, for instance, blockages such as in urban cities, unmanned aerial vehicles (UAVs) can be considered as an alternative for providing and enhancing connectivity, particularly when IoT devices (IoTD) are constrained with their resources. Also, to conserve energy, IoTDs are assumed to alternate between their active and passive modes. This paper, therefore, considers a time-constrained data gathering problem from a network of sensing devices and with assistance from a UAV. A Reconfigurable Intelligent Surface (RIS) is deployed to further improve both the connectivity and energy efficiency of the UAV, particularly when multiple devices are served concurrently and experience different channel impairments. This integrated problem brings challenges related to the configuration of the phase shift elements of the RIS, the scheduling of IoTDs transmissions as well as the trajectory of the UAV. First, the problem is formulated with the objective of maximizing the total number of served devices each during its activation period. Owing to its complexity and the incomplete knowledge about the environment, we leverage deep reinforcement learning in our solution; the UAV trajectory planning is modeled as a Markov Decision Process, and Proximal Policy Optimization is invoked to solve it. Next, the RIS configuration is then handled via Block Coordinate Descent.

eess.IV↗

arXiv2021

Joint Resource Allocation and Phase Shift Optimization for RIS-Aided eMBB/URLLC Traffic Multiplexing

This paper studies the coexistence of enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communication (URLLC) services in a cellular network that is assisted by a reconfigurable intelligent surface (RIS). The system model consists of one base station (BS) and one RIS that is deployed to enhance the performance of both eMBB and URLLC in terms of the achievable data rate and reliability, respectively. We formulate two optimization problems, a time slot basis eMBB allocation problem and a mini-time slot basis URLLC allocation problem. The eMBB allocation problem aims at maximizing the eMBB sum rate by jointly optimizing the power allocation at the BS and the RIS phase-shift matrix while satisfying the eMBB rate constraint. On the other hand, the URLLC allocation problem is formulated as a multi-objective problem with the goal of maximizing the URLLC admitted packets and minimizing the eMBB rate loss. This is achieved by jointly optimizing the power and frequency allocations along with the RIS phase-shift matrix. In order to avoid the violation in the URLLC latency requirements, we propose a novel framework in which the RIS phase-shift matrix that enhances the URLLC reliability is proactively designed at the beginning of the time slot. For the sake of solving the URLLC allocation problem, two algorithms are proposed, namely, an optimization-based URLLC allocation algorithm and a heuristic algorithm. The simulation results show that the heuristic algorithm has a low time complexity, which makes it practical for real-time and efficient multiplexing between eMBB and URLLC traffic. In addition, using only 60 RIS elements, we observe that the proposed scheme achieves around 99.99\% URLLC packets admission rate compared to 95.6\% when there is no RIS, while also achieving up to 70\% enhancement on the eMBB sum rate.

eess.SP↗

arXiv2021

Reconfigurable Intelligent Surface Enabled Vehicular Communication: Joint User Scheduling and Passive Beamforming

Given its ability to control and manipulate wireless environments, reconfigurable intelligent surface (RIS), also known as intelligent reflecting surface (IRS), has emerged as a key enabler technology for the six-generation (6G) cellular networks. In the meantime, vehicular environment radio propagation is negatively influenced by a large set of objects that cause transmission distortion such as high buildings. Therefore, this work is devoted to explore the area of RIS technology integration with vehicular communications while considering the dynamic nature of such communication environment. Specifically, we provide a system model where RoadSide Unit (RSU) leverages RIS to provide indirect wireless transmissions to disconnected areas, known as dark zones. Dark zones are spots within RSU coverage where the communication links are blocked due to the existence of blockages. In details, a discrete RIS is utilized to provide communication links between the RSU and the vehicles passing through out-of-service zones. Therefore, the joint problem of RSU resource scheduling and RIS passive beamforming or phase-shift matrix is formulated as an optimization problem with the objective of maximizing the minimum average bit rate. The formulated problem is mixed integer non-convex program which is difficult to be solved and does not account for the uncertain dynamic environment in vehicular networks. Thereby, we resort to alternative methods based on Deep Reinforcement Learning to determine RSU wireless scheduling and Block Coordinate Descent (BCD) to solve for the phase-shift matrix, \textit{i.e.,} passive beamforming, of the RIS. The Markov Decision Process (MDP) is defined and the complexity of the solution approach is discussed. Our numerical results demonstrate the superiority of our proposed approach over baseline techniques.

eess.SP↗

arXiv2021

Integration of IRS in Indoor VLC Systems: Challenges, Potential and Promising Solutions

Visible light communication (VLC) is an optical wireless communication technology that is considered a promising solution for high-speed indoor connectivity. Unlike the case in conventional radio-frequency wireless systems, the VLC channel is not isotropic, meaning that the device orientation affects the channel gain significantly. In addition, due to the use of optical frequency bands, the presence of different obstacles (e.g., walls, human bodies, furniture) may easily block the VLC links. One solution to overcome these issues is the integration of the intelligent reflective surface (IRS), which is a new and revolutionizing technology that has the potential to significantly improve the performance of wireless networks. IRS is capable of smartly reconfiguring the wireless propagation environment with the use of massive low-cost passive reflecting elements integrated on a planar surface. In this paper, a framework for integrating IRS in indoor VLC systems is presented. We give an overview of IRS, including its advantages, different types and main applications in VLC systems, where we demonstrate the potential of IRS in overcoming the effects of random device orientation and links blockages. We discuss key factors pertaining to the design and integration of IRS in VLC systems, namely, the deployment of IRSs, the channel state information acquisition, the optimization of IRS configuration and the real-time IRS control. We also lay out a number of promising research directions that center around the integration of IRS in indoor VLC systems.

eess.SP↗

arXiv2021

Reconfigurable Intelligent Surface Enabled Full-Duplex/Half-Duplex Cooperative Non-Orthogonal Multiple Access

This paper investigates the downlink transmission of reconfigurable intelligent surface (RIS)-aided cooperative non-orthogonal-multiple-access (C-NOMA), where both half-duplex (HD) and full-duplex (FD) relaying modes are considered. The system model consists of one base station (BS), two users and one RIS. The goal is to minimize the total transmit power at both the BS and at the user-cooperating relay for each relaying mode by jointly optimizing the power allocation coefficients at the BS, the transmit power coefficient at the relay user, and the passive beamforming at the RIS, subject to power budget constraints, the successive interference cancellation constraint and the minimum required quality-of-service at both cellular users. To address the high-coupled optimization variables, an efficient algorithm is proposed by invoking an alternating optimization approach that decomposes the original problem into a power allocation sub-problem and a passive beamforming sub-problem, which are solved alternately. For the power allocation sub-problem, the optimal closed-form expressions for the power allocation coefficients are derived. Meanwhile, the semi-definite relaxation approach is exploited to tackle the passive beamforming sub-problem. The simulation results validate the accuracy of the derived power control closed-form expressions and demonstrate the gain in the total transmit power brought by integrating the RIS in C-NOMA networks.

eess.SP↗

arXiv2020

A Downlink Puncturing Scheme for Simultaneous Transmission of URLLC and eMBB Traffic by Exploiting Data Similarity

Ultra Reliable and Low Latency Communications (URLLC) is deemed to be an essential service in 5G systems and beyond to accommodate a wide range of emerging applications with stringent latency and reliability requirements. Coexistence of URLLC alongside other service categories calls for developing spectrally efficient multiplexing techniques. Specifically, coupling URLLC and conventional enhanced Mobile BroadBand (eMBB) through superposition/puncturing naturally arises as a promising option due to the tolerance of the latter in terms of latency and reliability. The idea here is to transmit URLLC packets over resources occupied by ongoing eMBB transmissions while minimizing the impact on the eMBB transmissions. In this paper, we propose a novel downlink URLLC-eMBB multiplexing technique that exploits possible similarities among URLLC and eMBB symbols, with the objective of reducing the size of the punctured eMBB symbols. We propose that the base station scans the eMBB traffic' symbol sequences and punctures those that have the highest symbol similarity with that of the URLLC users to be served. As the eMBB and URLLC may use different constellation sizes, we introduce the concept of symbol region similarity to accommodate the different constellations. We assess the performance of the proposed scheme analytically, where we derive closed-form expressions for the symbol error rate (SER) of the eMBB and URLLC services. {We also derive an expression for the eMBB loss function due to puncturing in terms of the eMBB SER}. We demonstrate through numerical and simulation results the efficacy of the proposed scheme where we show that 1) the eMBB spectral efficiency is improved by puncturing fewer symbols, 2) the SER and reliability performance of eMBB are improved, and 3) the URLLC data is accommodated within the specified delay constraint while maintaining its reliability.

eess.SP↗

arXiv2020

Optimizing Age of Information Through Aerial Reconfigurable Intelligent Surfaces: A Deep Reinforcement Learning Approach

We investigate the benefits of integrating unmanned aerial vehicles (UAVs) with reconfigurable intelligent surface (RIS) elements to passively relay information sampled by Internet of Things devices (IoTDs) to the base station (BS). In order to maintain the freshness of relayed information, an optimization problem with the objective of minimizing the expected sum Age-of-Information (AoI) is formulated to optimize the altitude of the UAV, the communication schedule, and phases-shift of RIS elements. In the absence of prior knowledge of the activation pattern of the IoTDs, proximal policy optimization algorithm is developed to solve this mixed-integer non-convex optimization problem. Numerical results show that our proposed algorithm outperforms all others in terms of AoI.

eess.SP↗

arXiv2020

Invoking Deep Learning for Joint Estimation of Indoor LiFi User Position and Orientation

Light-fidelity (LiFi) is a fully-networked bidirectional optical wireless communication (OWC) that is considered a promising solution for high-speed indoor connectivity. Unlike in conventional radio frequency wireless systems, the OWC channel is not isotropic, meaning that the device orientation affects the channel gain significantly. However, due to the lack of proper channel models for LiFi systems, many studies have assumed that the receiver is vertically upward and randomly located within the coverage area, which is not a realistic assumption from a practical point of view. In this paper, novel realistic and measurement-based channel models for indoor LiFi systems are proposed. Precisely, the statistics of the channel gain are derived for the case of randomly oriented stationary and mobile LiFi receivers. For stationary users, two channel models are proposed, namely, the modified truncated Laplace (MTL) model and the modified Beta (MB) model. For LiFi users, two channel models are proposed, namely, the sum of modified truncated Gaussian (SMTG) model and the sum of modified Beta (SMB) model. Based on the derived models, the impact of random orientation and spatial distribution of LiFi users is investigated, where we show that the aforementioned factors can strongly affect the channel gain and system performance.

eess.SP↗

arXiv2020

A Low-Complexity Framework for Joint User Pairing and Power Control for Cooperative NOMA in 5G and Beyond Cellular Networks

This paper investigates the performance of cooperative non-orthogonal multiple access (C-NOMA) in a cellular downlink system. The system model consists of a base station (BS) serving multiple users, where users with good channel quality can assist the transmissions between the BS and users with poor channel quality through either half-duplex (HD) or full-duplex (FD) device-to-device (D2D) communications. We formulate and solve a novel optimization problem that jointly determines the optimal D2D user pairing and the optimal power control scheme, where the objective is maximizing the achievable sum rate of the whole system while guaranteeing a certain quality of service (QoS) for all users. The formulated problem is a mixed-integer non-linear program (MINLP) which is generally NPhard. To overcome this issue, we reconstruct the original problem into a bi-level optimization problem that can be decomposed into two sub-problems to be solved independently. The outer problem is a linear assignment problem which can be efficiently handled by the well-known Hungarian method. The inner problem is still a non-convex optimization problem for which finding the optimal solution is challenging. However, we derive the optimal power control policies for both the HD and the FD schemes in closedform expressions, which makes the computational complexity of the inner problems polynomial for every possible pairing configurations. These findings solve ultimately the original MILNP in a timely manner that makes it suitable for real-time and low latency applications. Our simulation results show that the proposed framework outperforms a variety of proposed schemes in the literature and that it can obtain the optimal pairing and power control policies for a network with 100 users in a negligible computational time.

eess.SP↗

arXiv2020

Measurements-Based Channel Models for Indoor LiFi Systems

eess.SP↗

arXiv2019

Beamforming Learning for mmWave Communication: Theory and Experimental Validation

To establish reliable and long-range millimeter-wave (mmWave) communication, beamforming is deemed to be a promising solution. Although beamforming can be done in the digital and analog domains, both approaches are hindered by several constraints when it comes to mmWave communications. For example, performing fully digital beamforming in mmWave systems involves using many radio frequency (RF) chains, which are expensive and consume high power. This necessitates finding more efficient ways for using fewer RF chains while taking advantage of the large antenna arrays. One way to overcome this challenge is to employ (partially or fully) analog beamforming through proper configuration of phase-shifters. Existing works on mmWave analog beam design either rely on the knowledge of the channel state information (CSI) per antenna within the array, require a large search time (e.g., exhaustive search) or do not guarantee a minimum beamforming gain (e.g., codebook based beamforming). In this paper, we propose a beam design technique that reduces the search time and does not require CSI while guaranteeing a minimum beamforming gain. The key idea derives from observations drawn from real-life measurements. It was observed that for a given propagation environment (e.g., coverage area of a mmWave BS) the azimuthal angles of dominant signals could be more probable from certain angles than others. Thus, pre-collected measurements could used to build a beamforming codebook that regroups the most probable beam designs. We invoke Bayesian learning for measurements clustering. We evaluate the efficacy of the proposed scheme in terms of building the codebook and assessing its performance through real-life measurements. We demonstrate that the training time required by the proposed scheme is only 5% of that of exhaustive search. This crucial gain is obtained while achieving a minimum targeted beamforming gain.

cs.IT↗

arXiv2019

Physical Layer Security for Visible Light Communication Systems: A Survey

Due to the dramatic increase in high data rate services and in order to meet the demands of the fifth-generation (5G) networks, researchers from both academia and industry are exploring advanced transmission techniques, new network architectures and new frequency spectrum such as the visible light spectra. Visible light communication (VLC) particularly is an emerging technology that has been introduced as a promising solution for 5G and beyond. Although VLC systems are more immune against interference and less susceptible to security vulnerabilities since light does not penetrate through walls, security issues arise naturally in VLC channels due to their open and broadcasting nature, compared to fiber-optic systems. In addition, since VLC is considered to be an enabling technology for 5G, and security is one of the 5G fundamental requirements, security issues should be carefully addressed and resolved in the VLC context. On the other hand, due to the success of physical layer security (PLS) in improving the security of radio-frequency (RF) wireless networks, extending such PLS techniques to VLC systems has been of great interest. Only two survey papers on security in VLC have been published in the literature. However, a comparative and unified survey on PLS for VLC from information theoretic and signal processing point of views is still missing. This paper covers almost all aspects of PLS for VLC, including different channel models, input distributions, network configurations, precoding/signaling strategies, and secrecy capacity and information rates. Furthermore, we propose a number of timely and open research directions for PLS-VLC systems, including the application of measurement-based indoor and outdoor channel models, incorporating user mobility and device orientation into the channel model, and combining VLC and RF systems to realize the potential of such technologies.

eess.SP↗

arXiv2019

Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.

cs.NI↗

arXiv2018

Bidirectional Optical Spatial Modulation for Mobile Users: Towards a Practical Design for LiFi Systems

Among the challenges of realizing the full potential of light-fidelity (LiFi) cellular networks are user mobility, random device orientation and blockage. We study the impact of those challenges on the performance of LiFi in an indoor environment using measurement-based channel models. We adopt spatial modulation (SM), which has been shown to be energy efficient in many applications, including LiFi. We consider two configurations for placing the photodiodes (PDs) on the user equipment (UE). The first one is referred to as the screen receiver (SR) whereby all the PDs are located on one face of the UE, whereas the other one is a multi-directional receiver (MDR), in which the PDs are located on different sides of the UE. The latter configuration was motivated by the fact that SR exhibited poor performance in the presence of random device orientation and blockage. We show that MDR outperforms SR by over $10$ dB at BER of $3.8\times10^{-3}$. Moreover, an adaptive access point (AP) selection scheme for SM is considered where the number of APs are chosen adaptively in an effort to achieve the lowest energy requirement for a target BER and spectral efficiency. The user performance with random orientation and blockage in the whole room is evaluated for sitting and walking activities. For the latter, we invoke the orientation-based random waypoint (ORWP) mobility model. We also study the performance of the underlying system on the uplink channel where the same techniques are used for the downlink channel. Specifically, as the transmitted uplink power is constrained, the energy efficiency of SM is evaluated analytically. It is shown that the multi-directional transmitter (MDT) with adaptive SM is highly energy efficient. As a benchmark, we compare the performance of the proposed framework to that of the conventional spatial multiplexing system, and demonstrate the superiority of the proposed one.

eess.SP↗

arXiv2017

A Novel Algorithm for Optimal Electricity Pricing in a Smart Microgrid Network

The evolution of smart microgrid and its demand-response characteristics not only will change the paradigms of the century-old electric grid but also will shape the electricity market. In this new market scenario, once always energy consumers, now may act as sellers due to the excess of energy generated from newly deployed distributed generators (DG). The smart microgrid will use the existing electrical transmission network and a pay per use transportation cost without implementing new transmission lines which involve a massive capital investment. In this paper, we propose a novel algorithm to minimize the electricity price with the optimal trading of energy between sellers and buyers of the smart microgrid network. The algorithm is capable of solving the optimal power allocation problem (with optimal transmission cost) for a microgrid network in a polynomial time without modifying the actual marginal costs of power generation. We mathematically formulate the problem as a nonlinear non-convex and decompose the problem to separate the optimal marginal cost model from the electricity allocation model. Then, we develop a divide-and-conquer method to minimize the electricity price by jointly solving the optimal marginal cost model and electricity allocation problems. To evaluate the performance of the solution method, we develop and simulate the model with different marginal cost functions and compare it with a first come first serve electricity allocation method.

eess.SY↗

arXiv2017

On the Achievable Secrecy Diversity of Cooperative Networks with Untrusted Relays

Cooperative relaying is often deployed to enhance the communication reliability (i.e., diversity order) and consequently the end-to-end achievable rate. However, this raises several security concerns when the relays are untrusted since they may have access to the relayed message. In this paper, we study the achievable secrecy diversity order of cooperative networks with untrusted relays. In particular, we consider a network with an N-antenna transmitter (Alice), K single-antenna relays, and a single-antenna destination (Bob). We consider the general scenario where there is no relation between N and K, and therefore K can be larger than N. Alice and Bob are assumed to be far away from each other, and all communication is done through the relays, i.e., there is no direct link. Providing secure communication while enhancing the diversity order has been shown to be very challenging. In fact, it has been shown in the literature that the maximum achievable secrecy diversity order for the adopted system model is one (while using artificial noise jamming). In this paper, we adopt a nonlinear interference alignment scheme that we have proposed recently to transmit the signals from Alice to Bob. We analyze the proposed scheme in terms of the achievable secrecy rate and secrecy diversity order. Assuming Gaussian inputs, we derive an explicit expression for the achievable secrecy rate and show analytically that a secrecy diversity order of up to min(N,K)-1 can be achieved using the proposed technique. We provide several numerical examples to validate the obtained analytical results and demonstrate the superiority of the proposed technique to its counterparts that exist in the literature.

cs.CR↗