Mixed Fully-Digital and Subarray-Based Panels: Enhanced Pilot Reception for Analog Precoding

This paper proposes a novel mixed panel architecture for channel state information (CSI) acquisition from uplink (UL) channel training in hybrid analog-digital beamforming systems with partially-connected structures in time-division duplex massive multiple-input multiple-output networks. The proposed architecture combines a few fully-digital (FD) panels with a large number of subarray-based panels for UL pilot reception, addressing CSI acquisition challenges while balancing performance and power efficiency. We then develop a unified method that can utilize measurements from both panel types to estimate the required CSI for analog precoder design. In particular, by recognizing that the dominant eigenvector of the panel covariance matrix is crucial for analog precoding, we propose an orthogonal matching pursuit-type algorithm to estimate it by exploiting channel sparsity in the angular domain. Additionally, we introduce a data-driven technique to optimize analog combiners for subarray-based panels during UL pilot reception. Numerical experiments demonstrate that our proposed method approaches the performance of an all-FD-panel architecture for UL pilot training while maintaining the low complexity of all-subarray-based-panel structures