Channel Training for RIS-Aided Indoor Terahertz MIMO Systems

Abstract

Reconfigurable intelligent surface (RIS) is a powerful tool in assisting large-scale tera-hertz (THz) communication, especially when the line-of-sight (LoS) propagation link is blocked. However, when the base station (BS) antenna array and RIS panel are very large, the THz channel shifts from the well-known far-field model to the less-investigated near-field model. Conventional far-field based channel training mismatches with the near-field channel characteristics, which leads to significant performance loss. In this letter, we investigate the near-filed channel training for an indoor RIS aided THz communication system consisting of a THz BS, an RIS, and an user equipment (UE) that are geographically close to each other. A BS channel training method is designed based on particle swarm optimization (PSO), where the unified near-field channel model is accommodated. Simulation results verify the effectiveness of the proposed channel training. Moreover, with RIS illumination, the UE received signal-to-noise ratio (SNR) can be further improved under imperfect channel and localization.