Block turbo equalization for imperfect channel state information

We propose a soft-input soft-output block equalizer based on constrained minimum variance filters. In contrast to other schemes, our receiver is designed for imperfect channel state information and incorporates the statistics of the channel estimation error. Thereby, we distinguish between data independent and data dependent evaluation of the covariance matrix of the estimation error. We show that the performance of our block equalizer is significantly improved when considering the influence of the actual data symbols on the estimation error. The additional complexity compared to the case when ignoring the data dependency of the estimation error increases quadratically with the block length. We assess the performance of our equalizer for block Rayleigh fading channels via Monte Carlo simulation, employing turbo equalization and one-shot training-based channel estimation