Clustered Sparse Channel Estimation for Massive MIMO Systems by Expectation Maximization-Propagation (EM-EP)

We study the problem of downlink channel estimation in multi-user massive multiple input output (MIMO) systems. To this end, we consider use Bayesian compressive sensing approach which clustered sparse structure angular domain is employed to reduce pilot overhead. capture structure, employ a conditionally independent identically distributed Bernoulli-Gaussian prior on vector representing channel, and Markov its support vector. An expectation propagation (EP) algorithm developed approximate intractable joint distribution with from an exponential family. The then used for direct channel. EP assumes that model parameters are known priori. Since these unknown, estimate using maximization (EM) algorithm. combination EM referred as EM-EP reminiscent variational approach. Simulation results show proposed outperforms several recently-proposed algorithms literature.