Channel Estimation for Reconfigurable-Intelligent-Surface-Aided Multiuser Communication Systems Exploiting Statistical CSI of Correlated RIS–User Channels
Haochen Li, Zhiwen Pan, Bin Wang, Nan Liu, Xiaohu You
Abstract
Reconfigurable intelligent surface (RIS) is a promising candidate technology for the upcoming sixth-generation (6G) communication system for its ability to manipulate the wireless communication environment by controlling the coefficients of reflection elements (REs). However, since the RIS usually consists of a large number of passive REs, the pilot overhead for channel estimation in the RIS-aided system is prohibitively high. In this article, the channel estimation problem for an RIS-aided multiuser multiple-input–single-output (MISO) communication system with clustered users is investigated. First, to describe the correlated feature for RIS–user channels, a beam-domain channel model is developed for RIS–user channels. Then, a pilot reuse strategy is put forward to reduce the pilot overhead and decompose the channel estimation problem into several subproblems. Finally, by leveraging the correlated nature of RIS–user channels, an eigenspace projection (EP) algorithm is proposed to solve each subproblem, respectively. Simulation results show that the proposed EP channel estimation scheme can achieve accurate channel estimation with lower pilot overhead than existing schemes.