Abstract:This paper proposes an iterative Maximum A Posteriori (MAP) probability channel estimation algorithm for MIMO-OFDM systems. The receiver employs the soft systematic bits and soft parity bits of MAP decoding and feeds them back to the channel estimator through nonlinear mapping. To track the time-varying channel, the estimator adopts the Recursive Least Squares (RLS) adaptive filtering algorithm so as to improve the accuracy of the estimation. Computer simulations show that the proposed algorithm can achieve much better performance than the conventional Least Squares (LS) channel estimation in both Mean Square Error (MSE) and Frame Error Rate(FER) .