Information Theory MAP sequence equalization for imperfect frequency selective channel knowledge

This paper considers the problem of Maximum a Posteriori (MAP) sequence equalization over a frequency selective channel when the channel is not perfectly known at the receiver. The imperfect channel estimate is provided by a least squares estimator using a training sequence (TS). The derivation of the MAP criterion taking into account the channel estimation error exists in the literature but no direct practical implementation has been proposed. In this paper, we propose an approximate solution to the problem by using an iterative burst-by-burst equalizer based on the Expectation Maximization (EM) algorithm. Simulation results show that the performance of our iterative equalizer is significantly better than the performance of the non iterative equalizer which does not take into account the channel estimation error.