DOA Estimation for Coherent Multipath Signals with Covariance Matrix Reconstruction in Hybrid Massive Circular Array

Abstract

AbstractHybrid massive multiple-input multiple-output (MIMO) is regarded as a promising and economic technique to improve the spectral efficiency. However, regarding to the direction of arrival (DOA) estimation, the spatial covariance matrix cannot be obtained by conventional sample average algorithm in hybrid massive MIMO systems. Besides, the performance of DOA estimation can be affected dramatically by the multipath especially in railway scenarios. To address these issues, this paper proposes a two-dimensional (2-D) DOA estimation method based on covariance matrix reconstruction for coherent signals in hybrid massive MIMO systems, which combine the large circular antenna array with one-dimensional digital processing. We first carry out the coherent preprocessing by dividing the massive uniform-circular-arrays (UCAs) into four subarrays. Moreover, each submatrix is reconstructed and the arithmetic average of the reconstructed covariance matrices is calculated. Then, multiple signal classification (MUSIC) algorithm is introduced for the DOA estimation. Finally, the numerical results demonstrate that the proposed approach achieves a profound precision over the existing ones.KeywordsRailway mobile communicationHybrid massive circular arrayDOA estimationCoherent sourceCovariance matrix reconstruction