Robust turbo equalization - a minimax perspective

The linear equalization based turbo detection schemes often employ the conventional linear equalizers inherently designed under the assumption of perfect channel knowledge. In practical systems, where the knowledge of channel and the knowledge of interference correlations is available only as estimates, the use of such equalizers may lead to an uncontrolled degradation in system performance. In this work, we focus on the design of a priori information aware channel equalizer under the presence of an uncertainty about the channel knowledge and the knowledge of interference plus noise correlations. To this end, we pursue a minimax optimization procedure to design the equalizer such that it offers the best worst-case performance. We study the performance of the proposed minimax robust equalizer in comparison to the conventional equalizer, and analyze its convergence behavior, as a building block of the turbo equalization system, via EXIT charts.