Compressed Sensing and Kalman Filter Based Channel Tracking for mmWave Massive MIMO Systems

Millimeter wave (mmWave) communication system requires efficient yet accurate channel tracking to achieve high effective spectral efficiency. In this paper, we pay special attention to mmWave massive multiple-input multiple-output (MIMO) systems and propose a channel tracking approach based on compressed sensing and Kalman filter. To be specific, the proposed approach first utilizes compressed sensing technique to estimate the angular parameters, which tackles the grid mismatch and angle crossing. Subsequently, the angle prediction, beam training, and angle update are jointly designed by exploiting the temporal channel correlation, including different levels of channel variations. Simulation results show that the proposed channel tracking has higher spectral efficiency and lower tracking error than traditional methods for mmWave massive MIMO systems.