The State of AI-Empowered Backscatter Communications: A Comprehensive Survey

E-print/Working paper (2023)

The Internet of Things (IoT) is undergoing significant advancements, driven by the emergence of Backscatter Communication (BC) and Artificial Intelligence (AI). BC is an energy-saving and cost-effective ... [more ▼]

The Internet of Things (IoT) is undergoing significant advancements, driven by the emergence of Backscatter Communication (BC) and Artificial Intelligence (AI). BC is an energy-saving and cost-effective communication method where passive backscatter devices communicate by modulating ambient Radio-Frequency (RF) carriers. AI has the potential to transform our way of communicating and interacting and represents a powerful tool for enabling the next generation of IoT devices and networks. By integrating AI with BC, we can create new opportunities for energy-efficient and low-cost communication and open the door to a range of innovative applications that were previously not possible. This paper brings these two technologies together to investigate the current state of AI-powered BC. We begin with an introduction to BC and an overview of the AI algorithms employed in BC. Then, we delve into the recent advances in AI-based BC, covering key areas such as backscatter signal detection, channel estimation, and jammer control to ensure security, mitigate interference, and improve throughput and latency. We also explore the exciting frontiers of AI in BC using B5G/6G technologies, including backscatter-assisted relay and cognitive communication networks, backscatter-assisted MEC networks, and BC with RIS, UAV, and vehicular networks. Finally, we highlight the challenges and present new research opportunities in AI-powered BC. This survey provides a comprehensive overview of the potential of AI-powered BC and its insightful impact on the future of IoT. [less ▲]

DRL-Assisted Delay Optimized Task Offloading in Automotive-Industry 5.0 based VECNs

in Journal of King Saud University - Computer and Information Sciences (2023)

The rapid growth of Automotive-Industry 5.0 and its emergence with beyond fifth-generation (B5G) communications, is making vehicular edge computing networks (VECNs) increasingly complex. The latency ... [more ▼]

The rapid growth of Automotive-Industry 5.0 and its emergence with beyond fifth-generation (B5G) communications, is making vehicular edge computing networks (VECNs) increasingly complex. The latency constraints of modern automotive applications make it difficult to run complex applications on vehicle on-board units (OBUs). While multi-access edge computing (MEC) can facilitate task offloading to execute these applications, it is still a challenge to access them promptly and optimally. Traditional algorithms struggle to guarantee accuracy in such dynamic environment, but deep reinforcement learning (DRL) methods offer improved accuracy, robustness, and real-time decision-making capabilities. In this paper, we propose a DRL-based mobility, contact, and load aware cooperative task offloading (DCTO) scheme. DCTO is designed for both cellular and mmWave radio access technologies (RATs), and both binary and partial offloading mechanisms. DCTO targets delay minimization by opportunistically switching RATs and offloading mechanisms. We consider relative efficacy and neutrality factors as key performance indicators and use them to derive the DRL agent’s reward function. Extensive evaluations demonstrate that the DCTO scheme exhibits a substantial enhancement in task success rate, with an increase from 2.61% to 21.34%. It also improves the efficacy factor from 1.38 to 3.52 and reduces the neutrality factor from 4.99 to 0.76. Furthermore, the average task processing time is reduced by a range of 3.77% to 24.15%. Additionally, the DCTO scheme outperforms the other evaluated schemes in terms of reward and TFPS ratio. [less ▲]

A Survey on STAR-RIS: Use Cases, Recent Advances, and Future Research Challenges

E-print/Working paper (2023)

The recent development of metasurfaces, which may enable several use cases by modifying the propagation environment, is anticipated to have a substantial effect on the performance of 6G wireless ... [more ▼]

The recent development of metasurfaces, which may enable several use cases by modifying the propagation environment, is anticipated to have a substantial effect on the performance of 6G wireless communications. Metasurface elements can produce essentially passive sub-wavelength scattering to enable a smart radio environment. STAR-RIS, which refers to reconfigurable intelligent surfaces (RIS) that can transmit and reflect concurrently (STAR), is gaining popularity. In contrast to the widely studied RIS, which can only reflect the wireless signal and serve users on the same side as the transmitter, the STAR-RIS can both reflect and refract (transmit), enabling 360-degree wireless coverage, thus serving users on both sides of the transmitter. This paper presents a comprehensive review of the STAR-RIS, with a focus on the most recent schemes for diverse use cases in 6G networks, resource allocation, and performance evaluation. We begin by laying the foundation for RIS (passive, active, STARRIS), and then discuss the STAR-RIS protocols, advantages, and applications. In addition, we categorize the approaches within the domain of use scenarios, which includes increasing coverage, enhancing physical layer security (PLS), maximizing sum rate, improving energy efficiency (EE), and reducing interference. Next, we will discuss the various strategies for resource allocation and measures for performance evaluation. We aimed to elaborate, compare, and evaluate the literature in terms of setup, channel characteristics, methodology, and objectives. In conclusion, we examine the open research problems and potential future prospects in this field. [less ▲]

Integration of NOMA with Reflecting Intelligent Surfaces: A Multi-cell Optimization with SIC Decoding Errors

E-print/Working paper (2023)

Reflecting intelligent surfaces (RIS) has gained significant attention due to its high energy and spectral efficiency in next-generation wireless networks. By using low-cost passive reflecting elements ... [more ▼]

Reflecting intelligent surfaces (RIS) has gained significant attention due to its high energy and spectral efficiency in next-generation wireless networks. By using low-cost passive reflecting elements, RIS can smartly reconfigure the signal propagation to extend the wireless communication coverage. On the other hand, non-orthogonal multiple access (NOMA) has been proven as a key air interface technique for supporting massive connections over limited resources. Utilizing the superposition coding and successive interference cancellation (SIC) techniques, NOMA can multiplex multiple users over the same spectrum and time resources by allocating different power levels. This paper proposes a new optimization scheme in a multi-cell RIS-NOMA network to enhance the spectral efficiency under SIC decoding errors. In particular, the power budget of the base station and the transmit power of NOMA users while the passive beamforming of RIS is simultaneously optimized in each cell. Due to objective function and quality of service constraints, the joint problem is formulated as non-convex, which is very complex and challenging to obtain the optimal global solution. To reduce the complexity and make the problem tractable, we first decouple the original problem into two sub-problems for power allocation and passive beamforming. Then, the efficient solution of each sub-problem is obtained in two-steps. In the first-step of For power allocation sub-problem, we transform it to a convex problem by inner approximation method and then solve it through a standard convex optimization solver in the second-step. Accordingly, in the first-step of passive beamforming, it is transformed to a standard semidefinite programming problem by successive convex approximation and different of convex programming methods. Then, penalty based method is used to achieve a Rank-1 solution for passive beamforming in second-step. Numerical results demonstrate the benefits of the proposed optimization scheme in the multi-cell RIS-NOMA network. [less ▲]

Ergodic Performance Analysis of Double Intelligent Reflecting Surfaces-Aided NOMA–UAV Systems with Hardware Impairment

in Drones (2022)

In this work, we design an intelligent reflecting surface (IRS)-assisted Internet of Things (IoT) by enabling non-orthogonal multiple access (NOMA) and unmanned aerial vehicles (UAV) approaches. We pay ... [more ▼]

In this work, we design an intelligent reflecting surface (IRS)-assisted Internet of Things (IoT) by enabling non-orthogonal multiple access (NOMA) and unmanned aerial vehicles (UAV) approaches. We pay attention to studying the achievable rates for the ground users. A practical system model takes into account the presence of hardware impairment when Rayleigh and Rician channels are adopted for the IRS–NOMA–UAV system. Our main findings are presented to showcase the exact expressions for achievable rates, and then we derive their simple approximations for a more insightful performance evaluation. The validity of these approximations is demonstrated using extensive Monte Carlo simulations. We confirm the achievable rate improvement decided by main parameters such as the average signal to noise ratio at source, the position of IRS with respect to the source and destination and the number of IRS elements. As a suggestion for the deployment of a low-cost IoT system, the double-IRS model is a reliable approach to realizing the system as long as the hardware impairment level is controlled. The results show that the proposed scheme can greatly improve achievable rates, obtain optimal performance at one of two devices and exhibit a small performance gap compared with the other benchmark scheme. [less ▲]

Intelligent and Secure Radio Environments for 6G Vehicular Aided HetNets: Key Opportunities and Challenges

in IEEE Communications standards Magazine (2022)

Reconfigurable meta-surfaces are emerging as a novel and revolutionizing technology to enable intelligent wireless environments. Due to the low cost, improved efficiency, and passive nature of reflecting ... [more ▼]

Reconfigurable meta-surfaces are emerging as a novel and revolutionizing technology to enable intelligent wireless environments. Due to the low cost, improved efficiency, and passive nature of reflecting elements, it is becoming possible to program and control the wireless environment. Since wireless physical layer technologies can generally adapt to the wireless environment, their combination with reconfigurable surfaces and deep learning approaches can open new avenues for achieving secure 6G vehicular aided heterogeneous networks (HetNets). Motivated by these appealing advantages, this work provides an intelligent and secure radio environment (ISRE) paradigm for 6G vehicular aided HetNets. We present an overview of enabling technologies for ISRE-based 6G vehicular aided HetNets. We discuss features, design goals, and applications of such networks. Next, we outline new opportunities provided by ISRE-based 6G vehicular HetNets and we present a case study using the contextual bandit approach in terms of best IRS for secure communications. Finally, we discuss some future research opportunities. [less ▲]

A Learning Based Framework for Enhancing Physical Layer Security in Cooperative D2D Network

in Electronics (2022)

Next-generation wireless communication networks demand high spectrum efficiency to serve the requirements of an enormous number of devices over a limited available frequency spectrum. Device-to-device ... [more ▼]

Next-generation wireless communication networks demand high spectrum efficiency to serve the requirements of an enormous number of devices over a limited available frequency spectrum. Device-to-device (D2D) communication with spectrum reuse offers a potential solution to spectrum scarcity. On the other hand, non-orthogonal multiple access (NOMA) as a multiple-access approach has emerged as a key technology to re-use a spectrum among multiple users. A cellular users (CUs) can share their spectrum with D2D users (DUs) and in response, the D2D network can help relay the CU signal to achieve better secrecy from an eavesdropper. Power optimization is known to be a promising technique to enhance system performance in challenging communication environments. This work aimed to enhance the secrecy rate of the CUs where the D2D transmitter (DT) helps in relaying the CU’s message under the amplify and forward (AF) protocol. A power optimization problem is considered under the quality of service constraints in terms of minimum rate requirements at the receivers and maximum power budgets at the transmitters. The problem is a non-convex complex optimization. A deep learning-based solution is proposed and promising results are obtained in terms of the secrecy rate of CU and the rate of D2D users. [less ▲]

Cooperative backscatter NOMA with imperfect SIC: Towards energy efficient sum rate maximization in sustainable 6G networks

in Journal of King Saud University - Computer and Information Sciences (2022), 34(10), 7940-7947

The combination of backscatter communication with non-orthogonal multiple access (NOMA) has the potential to support low-powered massive connections in upcoming sixth-generation (6G) wireless networks ... [more ▼]

The combination of backscatter communication with non-orthogonal multiple access (NOMA) has the potential to support low-powered massive connections in upcoming sixth-generation (6G) wireless networks. More specifically, backscatter communication can harvest and use the existing RF signals in the atmosphere for communication, while NOMA provides communication to multiple wireless devices over the same frequency and time resources. This paper has proposed a new resource management framework for backscatter-aided cooperative NOMA communication in upcoming 6G networks. In particular, the proposed work has simultaneously optimized the base station’s transmit power, relaying node, the reflection coefficient of the backscatter tag, and time allocation under imperfect successive interference cancellation to maximize the sum rate of the system. To obtain an efficient solution for the resource management framework, we have proposed a combination of the bisection method and dual theory, where the sub-gradient method is adopted to optimize the Lagrangian multipliers. Numerical results have shown that the proposed solution provides excellent performance. When the performance of the proposed technique is compared to a brute-forcing search technique that guarantees optimal solution however, is very time-consuming, it was seen that the gap in performance is actually 0%. Hence, the proposed framework has provided performance equal to a cumbersome brute-force search technique while offering much less complexity. The works in the literature on cooperative NOMA considered equal time distribution for cooperation and direct communication. Our results showed that optimizing the time-division can increase the performance by more than 110% for high transmission powers. [less ▲]

NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding

in IEEE Transactions on Intelligent Transportation Systems (2022)

To meet the demands of massive connections, diverse quality of services (QoS), ultra-reliable and low latency in the future sixth-generation (6G) Internet-of-vehicle (IoV) communications, we propose non ... [more ▼]

To meet the demands of massive connections, diverse quality of services (QoS), ultra-reliable and low latency in the future sixth-generation (6G) Internet-of-vehicle (IoV) communications, we propose non-orthogonal multiple access (NOMA)-enabled small-cell IoV network (SVNet). We aim to investigate the trade-off between system capacity and energy efficiency through a joint power optimization framework. In particular, we formulate a nonlinear multi-objective optimization problem under imperfect successive interference cancellation (SIC) detecting. Thus, the objective is to simultaneously maximize the sum-capacity and minimize the total transmit power of NOMA-enabled SVNet subject to individual IoV QoS, maximum transmit power and efficient signal detecting. To solve the nonlinear problem, we first exploit a weighted-sum method to handle the multi-objective optimization and then adopt a new iterative Sequential Quadratic Programming (SQP)-based approach to obtain the optimal solution. The proposed optimization framework is compared with Karush-Kuhn-Tucker (KKT)-based NOMA framework, average power NOMA framework, and conventional OMA framework. Monte Carlo simulation results unveil the validness of our derivations. The presented results also show the superiority of the proposed optimization framework over other benchmark frameworks in terms of system sum-capacity and total energy efficiency. [less ▲]

On reliability in the performance analysis of cognitive radio networks

in Journal of King Saud University - Computer and Information Sciences (2022)

Satisfying the quality of service (QoS) requirements of users in the form of channel availability and service retainability within the resource limited environment has been a major problem in cognitive ... [more ▼]

Satisfying the quality of service (QoS) requirements of users in the form of channel availability and service retainability within the resource limited environment has been a major problem in cognitive radio networks. In this connection, several research studies have been carried out in the literature to improve the QoS of users by proposing dynamic channel reservation algorithms. However, the studies have a number of limitations in their conceptual and mathematical modeling of channel availability and service retainability, which render their performance evaluation unreliable. In this paper, we address these limitations for leading to more realistic, reliable, and practically valid modeling. For conceptual modeling, we use connection availability in place of channel availability, motivated by the fact that the latter does not necessarily lead to a successful establishment of connection and, thus, is not a suitable performance indicator. For instance, obtaining a channel for transmission is of no avail if the intended receiver is inaccessible. Similarly, we consider service retainability with accessibility/inaccessibility of the intended receiver incorporated. For mathematical modeling, we use CTMC and the resultant closed from expressions to include all the required states of channel availability yet unsuccessful connection establishment. Additionally, we derive closed form equations for channel availability and service retainability that are in exact conformance with the CTMC model. Results confirm that considering the impact of receiver’s accessibility leads to performance difference for the channel availability and service retainability presented in the sate-of-the-art. [less ▲]