Common Sparsity and Cluster Structure Based Channel Estimation for Downlink Massive MIMO-OFDM Systems

In this letter, we propose a new channel estimation scheme for downlink channels in massive multiple-input multiple-output systems, where orthogonal frequency-division multiplexing is adopted. To estimate the downlink channels in the multi-subcarrier scenario, the common sparsity and cluster structure is exploited, which is unknown to the user. The common sparsity property is described and a local beta process is assumed on each of the common local clusters in a new constructed Bayesian framework. Then, we propose a common structure based multi-subcarrier Bayesian compressive sensing approach for the downlink channel estimation. Simulation results verify the effectiveness of the proposed algorithm.