NDLI: Space-time Chase decoding

Content Provider	IEEE Xplore Digital Library
Author	Love, D.J. Hosur, S. Batra, A. Heath Jr., R.W.
Copyright Year	2002
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.
Starting Page	2035
Ending Page	2039
Page Count	5
File Size	166290
File Format	PDF
ISSN	15361276
Volume Number	4
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maximum likelihood decoding MIMO Signal processing algorithms Maximum likelihood detection Maximum likelihood estimation Transmitting antennas Multidimensional systems Constellation diagram Yield estimation Wireless communication sphere decoding Chase decoding maximum-likelihood (ML) decoding multiple-input multiple-output (MIMO) systems spatial multiplexing
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering Computer Science Applications

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