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This paper proposes an iterative maximum a posteriori probability (MAP) receiver for multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) mobile communications. The receiver employs the expectation maximization (EM) algorithm so as to improve the performance of the approximated MAP detection, and applies adaptive algorithms such as the recursive least squares (RLS) and least mean square (LMS) algorithms to the channel estimation used in the EM algorithm in order to track a fast fading channel. For exploiting the space, time and frequency diversity, the low-density parity-check code (LDPC) is used as a channel coding with a built-in interleaver. Computer simulations under fast fading conditions show that the proposed receiver using the LMS algorithm can achieve better performance than the conventional minimum-mean-square-error (MMSE) channel estimation with much less computational complexity, and that the receiver using the RLS algorithm outperforms the ones with either the MMSE or the LMS algorithm.