Signal Power Maximization and Channel Estimation for mmWave Communication Systems Aided by RIS With Discrete Phase Shifts

Reconfigurable intelligent surfaces (RIS) have been advocated as a promising technology to overcome blockage issues in mmWave communications caused by severe propagation absorption and high directivity. This paper investigates the design of finite resolution phase shifters at the RIS to maximize the signal-to-noise ratio of a point-to-point multiple-input single output mmWave communication system. Both the transmitting antennas at the base station and the reflecting elements on the RIS are modeled as uniform planar arrays. The optimization of the discrete RIS design remains a computationally expensive procedure, especially for large reflecting surfaces and high resolution phase shifts. As a solution, we propose in this work a low-complexity suboptimal approach that exploits the structure of mmWave propagation channels. Specifically, the developed algorithms rely on decomposing the reflecting beamforming vectors and the channel path vectors into Kronecker products of factors of uni-modulus vectors. In addition to the computational complexity advantage, the proposed solutions also promise to require only partial information of the cascaded channel rather than the full one, the estimation of which is more practically convenient due to the passive nature of the RIS. To enable the proposed reflecting beamforming designs, we propose a channel estimation technique that invokes the atomic norm minimization framework to estimate the parameters of the channel, namely, the path’s magnitudes and their associated departure and arrival angles. Simulation results confirm the superiority of the proposed reflecting design and channel estimation scheme as compared to other existing techniques.