User Grouping based Structured Joint Sparse Channel Estimation for 3D MIMO System

Abstract

Accurate channel state information (CSI) is essential to fully unleash the potential of tree-dimensional multiple-input multiple output (3D MIMO) system. However, the computational complexity of channel estimation increases exponentially with the number of antennas. Fortunately, experiments reveal that there exists two kinds of structured common sparsity properties in massive 3D MIMO channel. One is the temporal domain common sparsity property shared by antennas, the other is the angular domain common sparsity property shared by multiple users. By jointly exploiting these two properties, we propose a user grouping based structured joint sparse channel estimation (UG-SJSCE) algorithm which can achieve significantly lower complexity. The simulation results show that compared with conventional CS algorithms, our proposed UG-SJSCE algorithm can achieve lower normalized mean squared error (NMSE).