Channel Estimation and Signal Recovery for RIS-empowered 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 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 L. Wei and C. Yuen are with the Engineering Product Development (EPD) Pillar, Singapore University of Technology and Design, Singapore 487372 (e-mails: wei li@mymail.sutd.edu.sg, yuenchau@sutd.edu.sg). C. Huang and Z. Zhang are with the College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310007, China, and Zhejiang Provincial Key Lab of Information Processing, Communication and Networking (IPCAN), Hangzhou 310007, China, and the International Joint Innovation Center, Zhejiang University, Haining 314400, China (e-mails: {chongwenhuang,ning ming}@zju.edu.cn). Q. Guo is with the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia (e-mail: qguo@uow.edu.au). Z. Yang is with the Centre for Telecommunications Research, Department of Engineering, King’s College London, WC2R, 2LS, UK (email: yang.zhaohui@kcl.ac.uk). M. Debbah is with CentraleSupélec, University Paris-Saclay, 91192 Gif-sur-Yvette, France. M. Debbah is also with the Lagrange Mathematics and Computing Research Center, Paris, 75007 France (email: merouane.debbah@huawei.com). ar X iv :2 10 6. 14 39 1v 1 [ cs .I T ] 2 8 Ju n 20 21