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Multiple signal classification (MUSIC) has been widely applied inmultiple-input multiple-output (MIMO) receivers for direction-of-arrival (DOA)estimation. To reduce the cost of radio frequency (RF) chains operating atmillimeter-wave bands, hybrid analog-digital structure has been adopted inmassive MIMO transceivers. In this situation, the received signals at theantennas are unavailable to the digital receiver, and as a consequence, thespatial covariance matrix (SCM), which is essential in MUSIC algorithm, cannotbe obtained using traditional sample average approach. Based on our previouswork, we propose a novel algorithm for SCM reconstruction in hybrid massiveMIMO systems with multiple RF chains. By switching the analog beamformers to agroup of predetermined DOAs, SCM can be reconstructed through the solutions ofa set of linear equations. In addition, based on insightful analysis on thatlinear equations, a low-complexity algorithm, as well as a careful selection ofthe predetermined DOAs, will be also presented in this paper. Simulationresults show that the proposed algorithms can reconstruct the SCM accurately sothat MUSIC algorithm can be well used for DOA estimation in hybrid massive MIMOsystems with multiple RF chains.

Spatial Covariance Matrix Reconstruction for DOA Estimation in Hybrid Massive MIMO Systems with Multiple Radio Frequency Chains