Joint Channel Estimation and Signal Recovery for RIS-Empowered Multiuser Communications

Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and low-power configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large num...

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Vydané v:IEEE transactions on communications Ročník 70; číslo 7; s. 4640 - 4655
Hlavní autori: Wei, Li, Huang, Chongwen, Guo, Qinghua, Yang, Zhaohui, Zhang, Zhaoyang, Alexandropoulos, George C., Debbah, Merouane, Yuen, Chau
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.07.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Approximation algorithms
Channel estimation
Gaussian approximation
Inference algorithms
Message passing
message passing algorithms
Network latency
Reconfigurable intelligent surfaces
Recovery
Series expansion
Signal reconstruction
signal recovery
Taylor series
Technological innovation
Training
Wireless communication
Wireless communication systems
Wireless networks
ISSN:0090-6778, 1558-0857
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Shrnutí:Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and low-power configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large number of unknown variables referring to the RIS unit elements and the transmitted signals, channel estimation and signal recovery in RIS-based systems are the ones of the most critical technical challenges. To address this problem, we focus on the RIS-assisted wireless communication system and present two joint channel estimation and signal recovery schemes based on message passing algorithms in this paper. Specifically, the proposed bidirectional scheme applies the Taylor series expansion and Gaussian approximation to simplify the sum-product procedure in the formulated problem. In addition, the inner iteration that adopts two variants of approximate message passing algorithms is incorporated to ensure robustness and convergence. Two ambiguities removal methods are also discussed in this paper. Our simulation results show that the proposed schemes show the superiority over the state-of-art benchmark method. We also provide insights on the impact of different RIS parameter settings on the proposed schemes.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2022.3179771