Abstract
When considering time-varying MIMO communication systems, there were a lot of researchers dedicating to the study of the robust equalizer to combat the problem caused by channel uncertainty. The most popular approaches to design a robust equalizer are the Bayesian approach and the minimax approach. However, the conventional robust equalizer is sometimes too conservative, which means it may not respond to time-varying channel very well, since they would always consider only the average uncertainty and worst-case uncertainty in the Bayesian approach and the minimax approach, respectively. In this study, we develop a suboptimal minimax-combining equalizer to cover all possible timevarying MIMO channels, which is modeled as a channel uncertain state switching system in Markov transition. Due to the idea of suboptimal design, the proposed equalizer extends the conventional MMSE equalizer to the robust combining equalizer. This proposed equalizer will deal with the multiple uncertainty ranges via minimax approach, and then the robust equalization results with respect to distinct uncertainty ranges are combined together by weightings based on likelihood function and the channel transition probabilities as the output. The combination equalization involves the switching probability between the multiple channel uncertain states and the likelihood functions. The advantage of the switching system modeling is that when the time-varying channel falls into a certain channel uncertain state, then a more suitable equalizer can be found. When combining the multiple equalizers, the likelihood function is defined so that give the more probable equalizers larger weightings.