Semiblind joint channel estimation and equalization for OFDM systems in rapidly varying channels

We describe a new joint iterative channel estimation and equalization algorithm for joint channel estimation and data detection for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and rapidly time-varying channels. The algorithm is based on the expectation maximization-maximum a posteriori (EM-MAP) technique which is very suitable for the multicarrier signal formats. The algorithm leads to a receiver structure that yields the equalized output, using the channel estimates. The pilot symbols are employed to estimate the initial channel coefficients effectively and unknown data symbols are averaged out in the algorithm. The band-limited, discrete cosine serial expansion of low dimensionality is employed to represent the time-varying fading channel. In this way, the resulting reduced dimensional channel coefficients are estimated iteratively with tractable complexity. The extensive computer simulations show that the algorithm has excellent symbol error rate (SER) and mean square error (MSE) performances for very high mobility even during the initialization step.