Blind Beamforming for RIS-aided High-Speed Train Communication with Doppler Pre-Compensation

High-speed train (HST) communications with reconfigurable intelligent surface (RIS) techniques have caused extensive research in recent years. In this paper, we study the RIS-aided HST scenario, considering Doppler pre-compensation at the base station (BS), and then align the RIS beam with the train without channel estimation. Firstly, we study and modify a blind beamforming algorithm for static scenarios and propose a new algorithm for HST scenarios. Considering the bad effect of Doppler frequency offset, caused by the high speed of the train, on system performance, and the predictability of the train track, we intend to use the Kalman filter to estimate train state information (including position and speed) in a single time step. Based on the estimated velocity, the Doppler effect is pre-compensated at the BS. According to the simulation results, we find the proposed algorithm can achieve the signal-to-noise ratio boost of the original algorithm under the condition of reduced complexity.