Bipolar Phase Shifts of Reconfigurable Intelligent Surface for Channel Estimation in RIS-Aided Multiuser mmWave Communications

Reconfigurable intelligent surface (RIS) is a key enabler for 6G wireless networks, reconfiguring wireless propagation to enhance the quality of signal transmission. In RIS-aided communications, channel estimation plays a crucial role because the performance improvement from RIS relies on the accuracy of channel state information. In this paper, we configure the phase shifts of RIS passive reflective elements, in an effort to improve the performance of cascaded channel estimation between a base station and users through the RIS in multiuser mmWave communications. We first apply the Golay complementary sequences to configure the bipolar phase shifts of RIS in training phase. Then, we study a theoretical recovery guarantee for compressed sensing based channel estimation with the Golay-based bipolar phase shifts of RIS. Simulation results demonstrate that the Golay-based phase shift configuration exhibits excellent performance for channel estimation, outperforming random and optimized phase shifts. The algebraic configuration of phase shifts contributes to improving the performance of channel estimation efficiently through a large-scale RIS with bi-phase resolution in RIS-aided multiuser mmWave communications.