TY - JOUR
T1 - Phase Shift Design in RIS Empowered Wireless Networks
T2 - From Optimization to AI-Based Methods
AU - Li, Zongze
AU - Wang, Shuai
AU - Lin, Qingfeng
AU - Li, Yang
AU - Wen, Miaowen
AU - Wu, Yik Chung
AU - Poor, H. Vincent
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/9
Y1 - 2022/9
N2 - Reconfigurable intelligent surfaces (RISs) offer the potential to customize the radio propagation environment for wireless networks. To fully exploit the advantages of RISs in wireless systems, the phases of the reflecting elements must be jointly designed with conventional communication resources, such as beamformers, the transmit power, and computation time. However, due to the unique constraints on the phase shifts and the massive numbers of reflecting units and users in large-scale networks, the resulting optimization problems are challenging to solve. This paper provides a review of the current optimization methods and artificial-intelligence-based methods for handling the constraints imposed by RISs and compares them in terms of the solution quality and computational complexity. Future challenges in phase-shift optimization involving RISs are also described, and potential solutions are discussed.
AB - Reconfigurable intelligent surfaces (RISs) offer the potential to customize the radio propagation environment for wireless networks. To fully exploit the advantages of RISs in wireless systems, the phases of the reflecting elements must be jointly designed with conventional communication resources, such as beamformers, the transmit power, and computation time. However, due to the unique constraints on the phase shifts and the massive numbers of reflecting units and users in large-scale networks, the resulting optimization problems are challenging to solve. This paper provides a review of the current optimization methods and artificial-intelligence-based methods for handling the constraints imposed by RISs and compares them in terms of the solution quality and computational complexity. Future challenges in phase-shift optimization involving RISs are also described, and potential solutions are discussed.
KW - artificial intelligence
KW - numerical optimization
KW - reconfigurable intelligent surfaces
KW - resource allocation
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U2 - 10.3390/network2030025
DO - 10.3390/network2030025
M3 - Review article
AN - SCOPUS:85139511457
SN - 2673-8732
VL - 2
SP - 398
EP - 418
JO - Network
JF - Network
IS - 3
ER -