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

Journal Article


Abstract


  • 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.

Publication Date


  • 2022

Citation


  • Wei, L., Huang, C., Guo, Q., Yang, Z., Zhang, Z., Alexandropoulos, G. C., . . . Yuen, C. (2022). Joint Channel Estimation and Signal Recovery for RIS-Empowered Multiuser Communications. IEEE Transactions on Communications, 70(7), 4640-4655. doi:10.1109/TCOMM.2022.3179771

Scopus Eid


  • 2-s2.0-85131741677

Web Of Science Accession Number


Start Page


  • 4640

End Page


  • 4655

Volume


  • 70

Issue


  • 7

Abstract


  • 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.

Publication Date


  • 2022

Citation


  • Wei, L., Huang, C., Guo, Q., Yang, Z., Zhang, Z., Alexandropoulos, G. C., . . . Yuen, C. (2022). Joint Channel Estimation and Signal Recovery for RIS-Empowered Multiuser Communications. IEEE Transactions on Communications, 70(7), 4640-4655. doi:10.1109/TCOMM.2022.3179771

Scopus Eid


  • 2-s2.0-85131741677

Web Of Science Accession Number


Start Page


  • 4640

End Page


  • 4655

Volume


  • 70

Issue


  • 7