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Editorial Material
en
2022

Editorial

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en
2022
Vol 3 (1)
Vol. 3
DOI: 10.23919/icn.2022.0008

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Rui Zhang
Rui Zhang

The Chinese University of Hong Kong

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Linglong Dai
Chan‐Byoung Chae
Shi Jin
+2 more

Abstract

Reconfigurable Intelligent Surface (RIS), also known as intelligent reflecting surface or large intelligent surface, is an emerging new physical-layer technology in the field of wireless communications. The basic idea of RIS is to deploy a reconfigurable passive array in the environment to manipulate the propagation of electron-magnetic waves. RIS promises a new design paradigm for wireless communications, where the wireless propagation environment can be dynamically controlled, which is substantially different from the conventional design that focuses only on the transmitter and receiver. For RIS-aided wireless communications, some of the current methodologies in conventional communication systems need to be revised, and some novel solutions are required to realize the potential benefits of the RIS. Although the number of publications about RIS has recently sharply increased, there are still many challenging issues to be extensively investigated, such as the RIS channel modeling, fundamental performance limits, the system design, joint optimization of the RIS and the transceivers, channel state information acquisition, and interdisciplinary applications. The goal of this Special Issue on “Reconfigurable Intelligent Surface Aided Wireless Communications” of Intelligent and Converged Networks (ICN) is to attract high-quality papers of original research on RIS-aided wireless communications. The response from the community to the call has been overwhelming. Many of the submissions are from the most well known research groups in the field. After a strict review process, we decided to accept 8 papers, which were selected based on the technical relevance and merits.

How to cite this publication

Linglong Dai, Chan‐Byoung Chae, Shi Jin, Marco Di Renzo, Rui Zhang (2022). Editorial. , 3(1), DOI: https://doi.org/10.23919/icn.2022.0008.

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Publication Details

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Editorial Material

Year

2022

Authors

5

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.23919/icn.2022.0008

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