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WSDSBL Method for Wideband Channel Estimation in Millimeter-Wave MIMO Systems with Lens Antenna Array

Jicheng Dong, Wei Zhang, Bowen Yang, and Xihong Sang
College of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, China

Abstract—In millimeter wave (mmWave) communication systems, Channel State Information(CSI) is extremely essential for beamforming. The traditional Successive Support Detection (SSD) algorithm can achieve high wideband channel estimation accuracy, but it only used least square (LS) algorithm to recover the detected channel part, the estimation accuracy is low under low SNR regions. To tackle this problem, in this paper, inspired by the classic Support Detection (SD) channel estimation scheme in narrowband, we propose an efficient Wideband Support Detection Sparse Bayesian Learning (WSDSBL) channel estimation scheme. For every subcarrier, we first detect the support of the wideband beamspace channel of the subcarrier, then we use the Sparse Bayesian Learning (SBL) scheme to recover it. Simulation results show that the proposed WSDSBL channel estimation algorithm is better than conventional wideband channel estimation schemes in MSE performance and achievable sum-rate performance, especially in low SNR regions.
 
Index Terms—Millimeter wave, channel state information, SSD, SBL, wideband channel estimation

Cite: Jicheng Dong, Wei Zhang, Bowen Yang, and Xihong Sang, "WSDSBL Method for Wideband Channel Estimation in Millimeter-Wave MIMO Systems with Lens Antenna Array," Journal of Communications vol. 15, no. 11, pp. 826-832, November 2020. Doi: 10.12720/jcm.15.11.826-832

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.