Reconfigurable Intelligent Surface for 6G Wireless Communications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 4491

Special Issue Editors

Queen Mary Univ London, Sch Elect Engn & Comp Sci, London E1 4NS, UK
Interests: reconfigurable intelligent surfaces (RIS); intelligent reflection surface (IRS); ultra-reliable low latency communication (URLLC); machine learning; UAV; internet of things; mobile edge computing
School of Cyber Science and Technology, Beihang University, Beijing 100191, China
Interests: reconfigurable intelligent surfaces (RIS); physical-layer security; mobile edge computing; space-air-ground networks
School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Interests: reconfigurable intelligent surfaces (RIS); terahertz (THz) communications; mobile edge computing

Special Issue Information

Dear Colleagues,

Every previous wireless generation has been designed based on the premise that the wireless environment is uncontrollable, and various advanced physical layer techniques have been designed to tackle its negative impact, such as severe signal attenuation, multiuser interference, and refractions and reflections from objects. A certain level of saturation has been reached in terms of capacity performance, which is not capable of supporting next-generation wireless applications that entail ultra-high spectral efficiency, ultra-reliability, and low-latency. As a result, it is imperative to develop a new technology that can control the wireless propagation environment.

Thanks to the recent breakthrough on metamaterials, reconfigurable intelligent surfaces (RISs) have been proposed to be a promising technology that enables the intelligent control of the wireless propagation environment through integrated electronic circuits and software. This is passive and does not need active hardware such as an amplifier, AD/DA converter, etc. Hence, it is energy efficient, light, and has a small size that enables it to be installed on environmental objects.

This Special Issue aims to solicit the most recent advances in channel modeling, analysis, and design of RIS-aided wireless communication systems. The topic of interests include but are not limited to:

  • Channel modeling for RIS-aided wireless networks;
  • Robust transmission design based on imperfect channel state information/hardware impairment;
  • Theoretical performance analysis for RIS-aided wireless networks;
  • Channel estimation for RIS-aided wireless networks;
  • Deployment optimization for RIS-aided wireless networks;
  • Radio location/sensing with the aid of RIS;
  • Applications of RIS in high-frequency communications, such as mmWave/Terahertz communications;
  • AI-empowered RIS-aided wireless networks;
  • Integration of RIS into emerging wireless communication applications such as wireless power transfer, mobile edge computing, physical layer security, UAV communications, etc.;
  • Testbeds, experimental measurements in RIS-aided wireless networks.

Dr. Cunhua Pan
Dr. Tong Bai
Dr. Yijin Pan
Guest Editors

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Keywords

  • intelligent reflecting surface
  • reconfigurable intelligent surface
  • 6G wireless communications
  • massive MIMO
  • mmWave communications
  • AI
  • UAV communications

Published Papers (2 papers)

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Research

14 pages, 1095 KiB  
Article
Deep Reinforcement Learning for RIS-Aided Multiuser MISO System with Hardware Impairments
by Wenjie Ma, Liuchang Zhuo, Luchu Li, Yuhao Liu and Hong Ren
Appl. Sci. 2022, 12(14), 7236; https://0-doi-org.brum.beds.ac.uk/10.3390/app12147236 - 18 Jul 2022
Cited by 2 | Viewed by 1301
Abstract
In this paper, we study a reconfigurable intelligent surface (RIS)-aided multiuser MISO system with imperfect hardware, where the transceiver design is based on the statistical channel state information (CSI). Considering the transceiver hardware impairments (HWI), we aim to maximize the minimum average user [...] Read more.
In this paper, we study a reconfigurable intelligent surface (RIS)-aided multiuser MISO system with imperfect hardware, where the transceiver design is based on the statistical channel state information (CSI). Considering the transceiver hardware impairments (HWI), we aim to maximize the minimum average user data rate, where the precoding matrices at the base station (BS) and the reflecting phase shifts at the RIS are jointly optimized. Since the problem is nonconvex and the objective function cannot be derived in closed form, we adopt the deep deterministic policy gradient (DDPG) algorithm to deal with this challenging optimization problem, where we generate a set of CSI vectors in an offline way, and then these data sets are used to train the neural networks. The simulation results demonstrate the rapid convergence speed of the adopted DDPG algorithm and also emphasize that it is crucial to consider the HWI when optimizing the transceiver. Full article
(This article belongs to the Special Issue Reconfigurable Intelligent Surface for 6G Wireless Communications)
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25 pages, 1248 KiB  
Article
Positioning Information Based High-Speed Communications with Multiple RISs: Doppler Mitigation and Hardware Impairments
by Ke Wang, Chan-Tong Lam and Benjamin K. Ng
Appl. Sci. 2022, 12(14), 7076; https://0-doi-org.brum.beds.ac.uk/10.3390/app12147076 - 13 Jul 2022
Cited by 4 | Viewed by 2174
Abstract
In this paper, we consider a multiple reconfigurable intelligent surface (RIS)-assisted system using positioning information (PI) to explore the potential of Doppler effect mitigation and spectral efficiency (SE) enhancement in high-speed communications (HSC) in the presence of hardware impairments (HWI). In particular, we [...] Read more.
In this paper, we consider a multiple reconfigurable intelligent surface (RIS)-assisted system using positioning information (PI) to explore the potential of Doppler effect mitigation and spectral efficiency (SE) enhancement in high-speed communications (HSC) in the presence of hardware impairments (HWI). In particular, we first present a general multi-RIS-assisted system model for HSC with HWI. Then, based on PI, different phase shift optimization strategies are designed and compared for maximizing SE, eliminating Doppler spread, and maintaining a very low delay spread. Moreover, we compare the performance of different numbers of RISs with HWI in terms of SE and delay spread. Finally, we extend our channel model from line-of-sight to the Rician channel to demonstrate the effectiveness and robustness of our proposed scheme. Numerical results reveal that the HWI of RISs increases the delay spread, but has no impact on Doppler shift and spread. Additionally, the multiple RIS system not only suffers a more severe delay spread, but is limited in SE due to the HWI. When the number of RISs increases from 2 to 16, the range of average spectral efficiency and delay spread are from 4 to 4.6 Bit/s/Hz and from 0.7 μs to 2.5 μs, respectively. In contrast to conventional RIS-assisted systems that require channel estimation, the proposed PI-based RIS system offers simplicity without compromising effectiveness and robustness in both SE enhancement and Doppler mitigation. Full article
(This article belongs to the Special Issue Reconfigurable Intelligent Surface for 6G Wireless Communications)
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