Reduced-complexity equalization techniques for ISI and MIMO wireless channels in iterative decoding

Abstract

Two reduced-complexity soft-input soft-output trellis decoding techniques are presented in this paper for equalizing single-input single-output intersymbol interference (ISI) channels and multiple-input multiple-output (MIMO) frequency selective fading channels. Given a trellis representing an ISI channel, the soft-output M-algorithm (SOMA) reduces the complexity of equalization by retaining only the best M survivors at each trellis interval. The remaining survivors are discarded. The novelty of the SOMA is the use of discarded paths to obtain soft-information. Through a simple update-and-discard procedure, the SOMA extracts reliable soft-information from discarded paths which enables a large trellis to be successfully decoded with a relatively small value of M. To decode a trellis representing a MIMO frequency selective fading channel, two challenges are faced. Not only that the trellis has a large number of states, the number of branches per trellis interval is also enormous. The soft-output trellis/tree M-algorithm (SOTTMA) expands each trellis interval into a tree-like structure and performs the M-algorithm twice: once at each trellis interval to reduce the number of states and the other at each tree sub-level to remove unwanted branches. With the proposed technique, high-order trellises with million of branches per interval can be decoded with modest complexity.