An enhanced channel estimation algorithm for OFDM: combined EM algorithm and polynomial fitting

Estimating a channel that is subject to frequency selective Rayleigh fading is a challenging problem in an orthogonal frequency division multiplexing (OFDM) system. In this paper we propose an enhanced channel estimation algorithm that combines the EM-based algorithms proposed previously and a Least Squares polynomial fitting (LSPF) approach. The combined algorithm can efficiently estimate the channel response of an OFDM system operating in an environment with multipath fading and additive white Gaussian noise (AWGN). The algorithm can improve the channel estimate obtained from the EM-based algorithms by polynomial fitting. Simulation results show that the hit error rate (BER) as well as the mean square error (MSE) of the channel can be improved by the algorithm. In particular, with these additional computations and demodulation delay, the MSE can be made smaller than the Cramer-Rao lower bound (CRLB).