Covariance Matrix Reconstruction for DOA Estimation in Hybrid Massive MIMO Systems

Multiple signal classification (MUSIC) has been widely applied in wireless communications for direction-of-arrival (DOA) estimation. For massive multiple-input multiple-output (MIMO) systems operating at millimeter-wave bands, hybrid analog-digital structure has been adopted in transceiver design to reduce the cost of radio frequency chains. In hybrid massive MIMO systems, the received signals at the antennas are not sent to the receiver directly, and spatial covariance matrix, which is essential in MUSIC algorithm, is thus unavailable. As a consequence, MUSIC algorithm cannot be directly used in hybrid massive MIMO systems. In this letter, we propose a beam sweeping approach for spatial covariance matrix reconstruction in hybrid massive MIMO systems. In particular, analog beamformer switches the beam direction to a group of predetermined DOA angles in turn, and then the spatial covariance matrix can be reconstructed by solving a set of linear equations. Insightful analysis on the reconstruction accuracy is also presented in this letter. Simulation results show that the proposed approach can reconstruct the spatial covariance matrix accurately so that MUSIC algorithm can be well used for DOA estimation in hybrid massive MIMO systems.