Hybrid Analog and Digital Beamforming Design for Channel Estimation in Correlated Massive MIMO Systems

In this paper, we study the channel estimation problem in correlated massive multiple-input-multiple-output (MIMO) systems with a reduced number of radio-frequency (RF) chains. Importantly, other than knowledge correlation matrices, make no assumption as to structure channel. To address limitation RF chains, employ hybrid beamforming, comprising low dimensional digital beamformer followed by an analog implemented using phase shifters. Since there is dedicated chain per transmitter/receiver antenna, conventional techniques for fully-digital are impractical. By exploiting fact that entries uncorrelated its eigen-domain, seek estimate domain. Due limited typically performed multiple time slots. Under total energy budget, aim design transmit (precoder) and receive (combiner) each training slot, order minimum mean squared error criterion. end, choose precoder combiner slot such they aligned transmitter receiver eigen-directions, respectively. Further, derive water-filling-type expression optimal allocation at slot. This illustrates that, only significant components need be estimated. contrast, large almost equally distributed among all eigen-directions. Simulation results show proposed scheme can efficiently MIMO channels within few