Channel Estimation in Massive MIMO-OFDM with Multi-group Adjustable Phase Shift Pilots

Estimating massive multiple-input multiple-output - orthogonal frequency division multiplexing (MIMO-OFDM) channels with low pilot overhead presents a significant challenge. Leveraging channel sparsity and pilot argument information (PAI), we propose a multi-group adjustable phase shift pilot (MAPSP) channel estimation method aimed at reducing pilot overhead. We first introduce a sparse channel model in angle-delay domain. Then, we propose the approach of generating phase shift pilots by dividing user terminals (UT) into groups and explore channel estimation based on the sparse channel model. We demonstrate that pilot interference can be mitigated by phase scheduling and received signal pre-processing. Capitalizing on this property, we propose a MAPSP implementation scheme. Simulation results indicate that the proposed MAPSP technique achieves a lower mean square error (MSE) of estimation than APSP and significantly enhances spectral efficiency.

Channel Estimation in Massive MIMO-OFDM with Multi-group Adjustable Phase Shift Pilots

Yu Zhao, Li You, Jinke Tang, Mengyu Qian, Bin Jiang, Xiqi Gao, Southeast University