Enhanced EM-based channel estimation for MIMO-OFDM in highly mobile channels

An enhanced expectation-maximization (EM)-based iterative channel estimator for coping with channel time variation is proposed for mobile multiple-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. In the proposed scheme, the recursive least squares (RLS) algorithm is applied to track the time-varying channel impulse response (CIR) within several symbols. By using the tracked time-varying CIR, the ICI are constructed and then cancelled from the received signal, thus reducing their impactions on the channel estimation. Moreover, based on an over-sampled complex exponential basis expansion model (OCE-BEM), an improved channel predictor is derived in order to improve the initial channel estimates accuracy of the iterative estimator. Simulation results show that the proposed scheme outperforms the classic counterpart in time-varying scenarios with a smaller cost of complexity.