Space-time Chase decoding

TLDR: A modified version of the classic Chase decoder for multiple-antenna systems is proposed, which can be adjusted to have a fixed or variable complexity, while maintaining performance close to that of an ML decoder.

Abstract: Multiple-antenna wireless systems are of interest because they provide increased capacity over single-antenna systems. Several space-time signaling schemes have been proposed to make use of this increased capacity. Space-time techniques, such as space-time block coding and spatial multiplexing, can all be viewed as signaling with a multidimensional constellation. Because of the large capacity of multiple-input multiple-output (MIMO) channels, these multidimensional constellations often have large cardinalities. For this reason, it is impractical to perform optimal maximum-likelihood (ML) decoding for space-time systems, even for a moderate number of transmit antennas. In this paper, we propose a modified version of the classic Chase decoder for multiple-antenna systems. The decoder applies successive detection to yield an initial estimate of the transmitted bit sequence, constructs a list of candidate symbol vectors using this initial estimate, and then computes bit likelihood information over this list. Three algorithms are presented for constructing the candidate vector list. This decoder can be adjusted to have a fixed or variable complexity, while maintaining performance close to that of an ML decoder.