Semi-Blind Channel Estimation and Data Detection for Multi-Cell Massive MIMO Systems on Time-Varying Channels

We study the problem of semi-blind channel estimation and symbol detection in uplink multi-cell massive MIMO (multi-input multi-output) systems with spatially correlated time-varying channels. An algorithm based on expectation propagation (EP) is developed to iteratively approximate joint a posteriori distribution unknown matrix transmitted data symbols from an exponential family. This then used for direct symbols. A modified version popular Kalman filtering referred as KF-M also proposed which emerges our EP derivations. Performance smoothing followed by KF-M, here KS-M, examined. Simulation results demonstrate that error rate (SER) EP-based algorithms improve increase number base station antennas length frame. In particular, increasing frame, can mitigate effects pilot contamination well channels system pilot-overhead around 5%.