Iterative Channel Estimation with Moving Average Filter in OFDM Packet Transmission System

In this paper, we propose a computationally efficient iterative channel estimation algorithm for orthogonal frequency division multiplexing (OFDM) systems. The minimum mean square error (MMSE) algorithm known for optimal channel estimation or the iterative maximum a-posteriori (MAP) channel estimation algorithm has an excellent performance but their complexities are very high because of the calculation of inverse matrix and covariance matrix. On the other hand, the discrete Fourier transform (DFT)-based channel estimation algorithm is inferior to MMSE algorithm but it has the advantage of a relatively low complexity. We particularly focus on improving this DFT-based estimator by combing in iterative channel update with turbo decoding. The proposed algorithm uses a novel moving average filter in order to minimize the estimation error of the updated channel. Simulation results show that the proposed algorithm gives better performance compared with the original DFT-based algorithm