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This paper proposes novel channel estimation methods for an iterative maximum a posteriori (MAP) receiver. The targeted systems are low-density parity-check (LDPC)-coded multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) mobile communications. By reconsidering the joint processing of the iterative MAP receiver from the viewpoint of the message-passing algorithm in the factor graph, this paper theoretically derives the recursive least squares (RLS) algorithm with smoothing and removing (SR-RLS). The computational complexity of SR-RLS is about two to three times larger than that of the original RLS algorithm. Computer simulations under fast multipath fading conditions show that the MAP receiver using the proposed SR-RLS channel estimator outperforms the one using the conventional RLS channel estimator.