Channel Tracking for Uniform Rectangular Arrays in mmWave Massive MIMO Systems

Abstract

MmWave is a promising option for meeting the high data rate demand of 5G. However, the severe path loss needs to be compensated by extracting the channel state information (CSI) for beamforming gain. The CSI can be obtained by channel tracking in time-varying channel environment. In this paper, we present a two-stage channel tracking algorithm for time-varying channel of URAs in mmWave massive MIMO systems. The two-stage channel tracking algorithm focuses on obtaining accurate CSI. Firstly, the azimuth and elevation angles are easily estimated based on extending Kalman Filter to obtain the physical channel matrix. Then, the matrix factorization $(\mathrm{M}\Gamma)$ algorithm is proposed to calibrate the channel, which decrease the estimation error caused by EKF. Simulation results demonstrate that the performance of the proposed algorithm. The proposed channel tracking algorithm can reduce the symbol error rates and increase the tracking time compared with traditional channel tracking algorithms.