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Intelligent Reflecting Surfaces for 5G Communication and Beyond

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

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 17589

Special Issue Editors


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Guest Editor
Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: antenna design; microwave components design; wireless communications; evolutionary algorithms; machine learning
Special Issues, Collections and Topics in MDPI journals

grade E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: wireless communications; wireless power transfer and applications; optical wireless communications; communications for biomedical engineering; wireless security
Special Issues, Collections and Topics in MDPI journals
ELEDIA Research Center, ELEDIA@UniTN, University of Trento, DICAM - Department of Civil, Environmental, and Mechanical Engineering, Via Mesiano 77, 38123 Trento, Italy
Interests: antenna array design, processing, and characterization; synthesis of complex electromagnetic devices through system-by-design techniques; surrogate-assisted optimization; learning-by-example; deep learning
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, China
Interests: Internet of Things (IoT); edge computing; machine learning; computer vision; cyber physical systems; future Internet architecture and smart-energy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Reconfigurable intelligent surfaces (RISs) or intelligent reflecting surfaces (IRSs) are an emerging transmission technology for application in wireless communications. They can reconfigure the wireless propagation environment via software-control reflection. Following the recent breakthrough in the fabrication of programmable metamaterials, reconfigurable intelligent surfaces have the potential to fulfill the challenging vision for 6G networks and materialize seamless connections and intelligent software-based control of the environment in wireless communication systems. Since IRS reflection beamforming prediction requires the perfect and imperfect channel knowledge, channel estimation is a crucial aspect for predicting IRS interaction matrices. In this context, IRS is combined with machine learning (ML) techniques, which are particularly powerful in providing channel estimation. This Special Issue aims at publishing high-quality research papers, as well as review articles addressing recent advances on IRS-aided wireless communications for 5G and beyond. Potential topics include but are not limited to the following:

  • IRS antenna design;
  • IRS channel modeling;
  • IRS channel capacity and performance limits;
  • IRS and ML techniques;
  • IRS channel estimation and channel feedback;
  • IRS indoor channel characterization;
  • IRS and NOMA techniques;
  • IRS prototyping and experimental results;
  • Cross-layer design for IRS-aided communications;
  • IRS and wireless power transfer communication;
  • IRS and mobile edge computing systems;
  • IRS and physical layer security techniques;
  • IRS and vehicle communications;
  • IRS transmissive and hybrid.

Relevant Journals could be visited: https://www.mdpi.com/journal/technologies/special_issues/Intelligent_5G

Prof. Dr. Sotirios K. Goudos
Prof. Dr. George Karagiannidis
Dr. Marco Salucci
Prof. Dr. Shaohua Wan
Guest Editors

Manuscript Submission Information

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Keywords

  • intelligent reflecting surfaces
  • reconfigurable intelligent surfaces
  • 5G
  • 6G
  • machine learning

Published Papers (4 papers)

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Research

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18 pages, 431 KiB  
Article
Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity
by Yoghitha Ramamoorthi, Masashi Iwabuchi, Tomoki Murakami, Tomoaki Ogawa and Yasushi Takatori
Sensors 2022, 22(15), 5755; https://doi.org/10.3390/s22155755 - 01 Aug 2022
Cited by 2 | Viewed by 1427
Abstract
The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagnetic properties of [...] Read more.
The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS-assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an α-fair utility function, the joint resource allocation and the user scheduling of a RIS-assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. A heuristic is proposed to solve the formulated optimization problem with the derived optimal user scheduling time fractions. Exhaustive simulation results for coverage and throughput of the RIS-assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS-assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems. Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G Communication and Beyond)
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14 pages, 867 KiB  
Communication
Sum Rate Optimization of IRS-Aided Uplink Muliantenna NOMA with Practical Reflection
by Jihyun Choi, Luiggi Cantos, Jinho Choi and Yun Hee Kim
Sensors 2022, 22(12), 4449; https://doi.org/10.3390/s22124449 - 12 Jun 2022
Cited by 5 | Viewed by 1594
Abstract
Recently, intelligent reflecting surfaces (IRSs) have drawn huge attention as a promising solution for 6G networks to enhance diverse performance metrics in a cost-effective way. For massive connectivity toward a higher spectral efficiency, we address an intelligent reflecting surface (IRS) to an uplink [...] Read more.
Recently, intelligent reflecting surfaces (IRSs) have drawn huge attention as a promising solution for 6G networks to enhance diverse performance metrics in a cost-effective way. For massive connectivity toward a higher spectral efficiency, we address an intelligent reflecting surface (IRS) to an uplink nonorthogonal multiple access (NOMA) network supported by a multiantenna receiver. We maximize the sum rate of the IRS-aided NOMA network by optimizing the IRS reflection pattern under unit modulus and practical reflection. For a moderate-sized IRS, we obtain an upper bound on the optimal sum rate by solving a determinant maximization (max-det) problem after rank relaxation, which also leads to a feasible solution through Gaussian randomization. For a large number of IRS elements, we apply the iterative algorithms relying on the gradient, such as Broyden–Fletcher–Goldfarb–Shanno (BFGS) and limited-memory BFGS algorithms for which the gradient of the sum rate is derived in a computationally efficient form. The results show that the max-det approach provides a near-optimal performance under unit modulus reflection, while the gradient-based iterative algorithms exhibit merits in performance and complexity for a large-sized IRS with practical reflection. Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G Communication and Beyond)
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Review

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21 pages, 15242 KiB  
Review
Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review
by Mohammad Abrar Shakil Sejan, Md Habibur Rahman, Beom-Sik Shin, Ji-Hye Oh, Young-Hwan You and Hyoung-Kyu Song
Sensors 2022, 22(14), 5405; https://doi.org/10.3390/s22145405 - 20 Jul 2022
Cited by 36 | Viewed by 6731
Abstract
An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. [...] Read more.
An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. In addition, machine learning (ML) techniques are now widely adopted in wireless communication as the computation power of devices has increased. As it is an emerging topic, we provide a comprehensive overview of the state-of-the-art on ML, especially on deep learning (DL)-based IRS-enhanced communication. We focus on their operating principles, channel estimation (CE), and the applications of machine learning to IRS-enhanced wireless networks. In addition, we systematically survey existing designs for IRS-enhanced wireless networks. Furthermore, we identify major issues and research opportunities associated with the integration of IRS and other emerging technologies for applications to next-generation wireless communication. Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G Communication and Beyond)
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30 pages, 6403 KiB  
Review
Intelligent Reflecting Surfaces Assisted UAV Communications for Massive Networks: Current Trends, Challenges, and Research Directions
by Syed Agha Hassnain Mohsan, Muhammad Asghar Khan, Mohammed H. Alsharif, Peerapong Uthansakul and Ahmed A. A. Solyman
Sensors 2022, 22(14), 5278; https://doi.org/10.3390/s22145278 - 14 Jul 2022
Cited by 29 | Viewed by 6561
Abstract
An intelligent reflecting surface (IRS) can intelligently configure wavefronts such as amplitude, frequency, phase, and even polarization through passive reflections and without requiring any radio frequency (RF) chains. It is predicted to be a revolutionizing technology with the capability to alter wireless communication [...] Read more.
An intelligent reflecting surface (IRS) can intelligently configure wavefronts such as amplitude, frequency, phase, and even polarization through passive reflections and without requiring any radio frequency (RF) chains. It is predicted to be a revolutionizing technology with the capability to alter wireless communication to enhance both spectrum and energy efficiencies with low expenditure and low energy consumption. Similarly, unmanned aerial vehicle (UAV) communication has attained a significant interest by research fraternity due to high mobility, flexible deployment, and easy integration with other technologies. However, UAV communication can face obstructions and eavesdropping in real-time scenarios. Recently, it is envisaged that IRS and UAV can combine together to achieve unparalleled opportunities in difficult environments. Both technologies can achieve enhanced performance by proactively altering the wireless propagation through maneuver control and smart signal reflections in three-dimensional space. This study briefly discusses IRS-assisted UAV communications. We survey the existing literature on this emerging research topic for both ground and airborne scenarios. We highlight several emerging technologies and application scenarios for future wireless networks. This study goes one step further to elaborate research opportunities to design and optimize wireless systems with low energy footprint and at low cost. Finally, we shed some light on open challenges and future research directions for IRS-assisted UAV communication. Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G Communication and Beyond)
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