Improved MIMO detection based on successive tree approximations

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Abstract

This paper proposes an efficient high-performance detection algorithm for MIMO communication systems that is based on a sequence of optimal tree approximations of the Gaussian density of the unconstrained linear system. The finite-set constraint is then applied to obtain a cycle-free discrete distribution that is suitable for message-passing algorithms. The proposed GTA-SIC algorithm is iterative and is based on first decoding the most reliable symbol, then canceling its contribution and applying the message-passing decoding to the smaller system. The computational complexity of the proposed GTA-SIC algorithm and the MMSE-SIC are comparable. The significantly improved MIMO decoding performance of the algorithm proposed here compared to lattice-reduction aided MMSE-SIC is demonstrated on several examples of large MIMO systems with high-order QAM constellations.

Original languageEnglish
Title of host publication2013 IEEE International Symposium on Information Theory, ISIT 2013
Pages2004-2008
Number of pages5
DOIs
StatePublished - 2013
Event2013 IEEE International Symposium on Information Theory, ISIT 2013 - Istanbul, Turkey
Duration: 7 Jul 201312 Jul 2013

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Conference

Conference2013 IEEE International Symposium on Information Theory, ISIT 2013
Country/TerritoryTurkey
CityIstanbul
Period7/07/1312/07/13

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