Abstract
We focus on the problem of reduced complexity equalization of multi-input, multi-output (MIMO) systems. In particular, we look at a prefilter design that enables the use of methods such as decision feedback sequence estimation (DFSE) while minimizing the effects of error propagation. We show that a well-known spectral factorization approach can be used to obtain a minimum-phase MIMO prefilter that performs energy compaction well, and thus provides a suitable prefilter. Through simulations on a MIMO system, we compare the performance of the minimum-phase MIMO prefilter with other prefilter approaches that have been published in literature, such as the minimum-mean-square (MMSE) and channel shortening prefilters. The minimum-phase MIMO prefilter outperforms the published approaches. In addition, the minimum-phase MIMO prefilter is less complex to compute.
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