A Novel SAGE-Based Channel Parameter Estimation Scheme for 6G RIS-Assisted Wireless Channel Measurements

As a promising key technology for the sixth generation (6G) wireless communication systems, the reconfigurable intelligent surface (RIS) is able to intelligently control the propagation environments. In order to investigate the properties of RIS-assisted channels, related channel measurements are necessary. However, the channel parameter estimation (CPE) work in RIS-assisted channel measurements is challenging since the RIS can only tune part of the channel. In this paper, we present a novel channel sounding procedure firstly where channels are observed through different RIS transmission modes. Then a space-alternating generalized expectation-maximization (SAGE) based CPE scheme for 6G RIS-assisted channel measurements is proposed, which is realized by the multipath components (MPCs) tracking and detection, the maximum likelihood (ML) estimation, and other procedures. It is capable of detecting whether MPCs interact with RIS and estimating all important channel parameters, including the angle parameters at the RIS side. Finally, the proposed scheme is evaluated through synthetic channels. The impacts of the RIS size, the number of transmission modes, and the phase quantization on its performance are investigated. Simulation results show a good performance of the proposed scheme.