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Reconfigurable Intelligent Surface-Aided MIMO Systems: Challenges and Trends

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (10 February 2024) | Viewed by 10218

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Special Issue Editors

Prof. Dr. Karim Seddik

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Guest Editor

Electronics and Communications Engineering Department, The American University in Cairo, Cairo 11835, Egypt
Interests: machine learning applications in communication networks; intelligent reflecting surfaces (IRS); age of information (AoI); back-scattered communications; layered channel coding; cognitive radio networks; massive MIMO

Dr. Hongliang Zhang

E-Mail Website
Guest Editor

Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, USA
Interests: cooperative communications; Internet of Things; aerial access networks; reconfigurable intelligent surfaces; optimization and game theory
Special Issues, Collections and Topics in MDPI journals

Dr. Radwa Sultan

E-Mail Website
Guest Editor

Electrical and Computer Engineering Department, Manhattan College, New York City, NY 10471, USA
Interests: intelligent reflecting surfaces; Internet of Things; massive MIMO; signal processing; wireless resource allocation

Special Issue Information

Dear Colleagues,

The recent development of reconfigurable intelligent surfaces (RIS) has challenged the perception that wireless communication environments are unmanageable. As a result, RIS has emerged as one of the most eminent technologies for the envisioned enhanced mobile broadband (eMBB) and massive machine-type communication required in for next-generation 6G networks. However, signal processing, channel acquisition, low-complexity system design, and adaptive optimization are all hurdles faced by the deployment of RIS in communication networks.

This Special Issue focuses on the current advances in RIS-assisted MIMO systems. Researchers are welcome to present original research on the advantages and limitations of using RIS in MIMO systems. Topics of interest include, but are not limited to, the following:

Channel modeling and estimations in RIS-aided MIMO systems;
Performance limits of RIS-aided MIMO systems;
Signal processing and machine learning for RIS-aided MIMO systems;
Deployment and network optimization for RIS-aided MIMO systems;
RIS-aided RF sensing and localization;
Low-complexity RIS-aided beamforming scheme;
Emerging applications of RISs;
Integration of RISs with existing wireless technologies (massive MIMO, millimeter-wave communication, THz communication, D2D communications, UAV communications, energy harvesting).

Prof. Dr. Karim Seddik
Dr. Hongliang Zhang
Dr. Radwa Sultan
Guest Editors

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Keywords

reconfigurable intelligent surfaces
channel modeling
passive beamforming
network optimization
machine learning
emerging applications
integration with existing wireless techniques

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Published Papers (5 papers)

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Research

28 pages, 3320 KiB

Open AccessArticle

Joint Beamforming and Phase Shifts Design for RIS-Aided Multi-User Full-Duplex Systems in Smart Cities

by Kunbei Pan, Bin Zhou, Wei Zhang and Cheng Ju

Sensors 2024, 24(1), 121; https://doi.org/10.3390/s24010121 - 25 Dec 2023

Cited by 1 | Viewed by 1269

Abstract

Full-duplex (FD) and reconfigurable intelligent surface (RIS) are potential technologies for achieving wireless communication effectively. Therefore, in theory, the RIS-aided FD system is supposed to enhance spectral efficiency significantly for the ubiquitous Internet of Things devices in smart cities. However, this technology additionally induces the loop-interference (LI) of RIS on the residual self-interference (SI) of the FD base station, especially in complicated urban outdoor environments, which will somewhat counterbalance the performance benefit. Inspired by this, we first establish an objective and constraints considering the residual SI and LI in two typical urban outdoor scenarios. Then, we decompose the original problem into two subproblems according to the variable types and jointly design the beamforming matrices and phase shifts vector methods. Specifically, we propose a successive convex approximation algorithm and a soft actor–critic deep reinforcement learning-related scheme to solve the subproblems alternately. To prove the effectiveness of our proposal, we introduce benchmarks of RIS phase shifts design for comparison. The simulation results show that the performance of the low-complexity proposed algorithm is only slightly lower than the exhaustive search method and outperforms the fixed-point iteration scheme. Moreover, the proposal in scenario two is more outstanding, demonstrating the application predominance in urban outdoor environments. Full article

(This article belongs to the Special Issue Reconfigurable Intelligent Surface-Aided MIMO Systems: Challenges and Trends)

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16 pages, 813 KiB

Open AccessArticle

Passive Beamforming Design of IRS-Assisted MIMO Systems Based on Deep Learning

by Hui Zhang, Qiming Jia, Meikun Li, Jingjing Wang and Yuxin Song

Sensors 2023, 23(16), 7164; https://doi.org/10.3390/s23167164 - 14 Aug 2023

Cited by 1 | Viewed by 1694

Abstract

In the intelligent reflecting surface (IRS)-assisted MIMO systems, optimizing the passive beamforming of the IRS to maximize spectral efficiency is crucial. However, due to the unit-modulus constraint of the IRS, the design of an optimal passive beamforming solution becomes a challenging task. The feature input of existing schemes often neglects to exploit channel state information (CSI), and all input data are treated equally in the network, which cannot effectively pay attention to the key information and features in the input. Also, these schemes usually have high complexity and computational cost. To address these issues, an effective three-channel data input structure is utilized, and an attention mechanism-assisted unsupervised learning scheme is proposed on this basis, which can better exploit CSI. It can also better exploit CSI by increasing the weight of key information in the input data to enhance the expression and generalization ability of the network. The simulation results show that compared with the existing schemes, the proposed scheme can effectively improve the spectrum efficiency, reduce the computational complexity, and converge quickly. Full article

(This article belongs to the Special Issue Reconfigurable Intelligent Surface-Aided MIMO Systems: Challenges and Trends)

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16 pages, 2715 KiB

Open AccessArticle

Learning-Based IRS-Assisted Secure Transmission for Mine IoTs

by Minghui Min, Jiayang Xiao, Peng Zhang, Jinling Song and Shiyin Li

Sensors 2023, 23(14), 6321; https://doi.org/10.3390/s23146321 - 12 Jul 2023

Cited by 3 | Viewed by 1664

Abstract

Mine Internet of Things (MIoT) devices in intelligent mines often face substantial signal attenuation due to challenging operating conditions. The openness of wireless communication also makes it susceptible to smart attackers, such as active eavesdroppers. The attackers can disrupt equipment operations, compromise production safety, and exfiltrate sensitive environmental data. To address these challenges, we propose an intelligent reflecting surface (IRS)-assisted secure transmission system for an MIoT device which enhances the security and reliability of wireless communication in challenging mining environments. We develop a joint optimization problem for the IRS phase shifts and transmit power, with the goal of enhancing legitimate transmission while suppressing eavesdropping. To accommodate time-varying channel conditions, we propose a reinforcement learning (RL)-based IRS-assisted secure transmission scheme that enables MIoT device to optimize both the IRS reflecting coefficients and transmit power for optimal transmission policy in dynamic environments. We adopt the deep deterministic policy gradient (DDPG) algorithm to explore the optimal transmission policy in continuous space. This can reduce the discretization error caused by traditional RL methods. The simulation results indicate that our proposed scheme achieves superior system utility compared with both the IRS-free (IF) scheme and the IRS randomly configured (IRC) scheme. These results demonstrate the effectiveness and practical relevance of our contributions, proving that implementing IRS in MIoT wireless communication can enhance safety, security, and efficiency in the mining industry. Full article

(This article belongs to the Special Issue Reconfigurable Intelligent Surface-Aided MIMO Systems: Challenges and Trends)

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16 pages, 4402 KiB

Open AccessArticle

Optimized Classification of Intelligent Reflecting Surface (IRS)-Enabled GEO Satellite Signals

by Mamoona Jamil, Mubashar Sarfraz, Sajjad A. Ghauri, Muhammad Asghar Khan, Mohamed Marey, Khaled Mohamad Almustafa and Hala Mostafa

Sensors 2023, 23(8), 4173; https://doi.org/10.3390/s23084173 - 21 Apr 2023

Viewed by 2485

Abstract

The intelligent reflecting surface (IRS) is a cutting-edge technology for cost-effectively achieving future spectrum- and energy-efficient wireless communication. In particular, an IRS comprises many low-cost passive devices that can independently reflect the incident signal with a configurable phase shift to produce three-dimensional (3D) passive beamforming without transmitting Radio-Frequency (RF) chains. Thus, the IRS can be utilized to greatly improve wireless channel conditions and increase the dependability of communication systems. This article proposes a scheme for an IRS-equipped GEO satellite signal with proper channel modeling and system characterization. Gabor filter networks (GFNs) are jointly proposed for the extraction of distinct features and the classification of these features. Hybrid optimal functions are used to solve the estimated classification problem, and a simulation setup was designed along with proper channel modeling. The experimental results show that the proposed IRS-based methodology provides higher classification accuracy than the benchmark without the IRS methodology. Full article

(This article belongs to the Special Issue Reconfigurable Intelligent Surface-Aided MIMO Systems: Challenges and Trends)

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30 pages, 727 KiB

Open AccessArticle

Robust Transceiver Design for IRS-Assisted Cascaded MIMO Communication Systems

by Hossein Esmaeili, Ali Kariminezhad and Aydin Sezgin

Sensors 2022, 22(17), 6587; https://doi.org/10.3390/s22176587 - 31 Aug 2022

Cited by 2 | Viewed by 1860

Abstract

Intelligent reconfigurable surfaces (IRSs) have gained much attention due to their passive behavior that can be a successor to relays in many applications. However, traditional relay systems might still be a perfect choice when reliability and throughput are the main concerns in a communication system. In this work, we use an IRS along with a decode-and-forward relay to provide a possible solution to address one of the main challenges of future wireless networks which is providing reliability. We investigate a robust transceiver design against the residual self-interference (RSI), which maximizes the throughput rate under self-interference channel uncertainty-bound constraints. The yielded problem turns out to be a non-convex optimization problem, where the non-convex objective is optimized over the cone of semidefinite matrices. We propose a novel mathematical method to find a lower bound on the performance of the IRS that can be used as a benchmark. Eventually, we show an important result in which, for the worst-case scenario, IRS can be helpful only if the number of IRS elements are at least as large as the size of the interference channel. Moreover, a novel method based on majorization theory and singular value decomposition (SVD) is proposed to find the best response of the transmitters and relay against worst-case RSI. Furthermore, we propose a multi-level water-filling algorithm to obtain a locally optimal solution iteratively. We show that our algorithm performs better that the state of the art in terms of time complexity as well as robustness. For instance, our numerical results show that the acheivable rate can be increased twofold and almost sixfold, respectively, for the case of small and large antenna array at transceivers. Full article

(This article belongs to the Special Issue Reconfigurable Intelligent Surface-Aided MIMO Systems: Challenges and Trends)

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