Channel estimation and hybrid precoding for distributed phased arrays based MIMO wireless communications

作     者：Zhang, Yu Huo, Yiming Wang, Dongming Dong, Xiaodai You, Xiaohu 

作者机构：National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Department of Electrical and Computer Engineering University of Victoria VictoriaBCV8P 5C2 Canada 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2019年

核心收录：

主　　题：MIMO systems 

摘      要：Distributed phased arrays based multiple-input multiple-output (DPA-MIMO) is a newly debuted architecture that enables both spatial multiplexing and beamforming while facilitating highly reconfigurable hardware implementation in millimeter-wave (mmWave) frequency bands. With a DPA-MIMO system, we focus on channel state information (CSI) acquisition and hybrid precoding. As benefited from a coordinated and open-loop pilot beam pattern design, all the subarrays can simultaneously perform channel sounding with less training overhead compared to the time-sharing operation of each subarray. Furthermore, two sparse channel recovery algorithms, known as joint orthogonal matching pursuit (JOMP) and joint sparse Bayesian learning with 2 reweighting (JSBL-2), are proposed to exploit the hidden structured sparsity in the beam-domain channel vector. Finally, successive interference cancellation (SIC) based hybrid precoding through subarray grouping is illustrated for the DPA-MIMO system, which decomposes the joint subarray RF beamformer design into an interactive per-subarray-group handle. Simulation results show that the proposed two channel estimators fully take advantage of the partial coupling characteristic of DPA-MIMO channels to perform channel recovery, and the proposed hybrid precoding algorithm is suitable for such array-of-subarrays architecture with satisfactory performance and low complexity. Copyright © 2019, The Authors. All rights reserved.