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This paper proposes a minimum mean square error (MMSE)-based algorithm for semi-blind estimation of a complex fading channel matrix. By approximating the channel product matrices to channel autocorrelation matrix, which is gained from the covariance matrix of the received data, a novel semi-blind algorithm named MMVE (MMSE to EVD technique) is rebuilt. The eigenvalue-eigenvector decomposition (EVD) is then used to simplify the new semi-blind OFDM channel estimation approach. Simulation results show that the algorithm outperforms conventional ML algorithm with respect to the MSE by 3dB. In comparison, the proposed method also harvests better BER performances.