A best-first tree-searching approach for ML decoding in MIMO system

Chung-An Shen, Ahmed M. Eltawil, Sudip Mondal, Khaled N. Salama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In MIMO communication systems maximum-likelihood (ML) decoding can be formulated as a tree-searching problem. This paper presents a tree-searching approach that combines the features of classical depth-first and breadth-first approaches to achieve close to ML performance while minimizing the number of visited nodes. A detailed outline of the algorithm is given, including the required storage. The effects of storage size on BER performance and complexity in terms of search space are also studied. Our result demonstrates that with a proper choice of storage size the proposed method visits 40% fewer nodes than a sphere decoding algorithm at signal to noise ratio (SNR) = 20dB and by an order of magnitude at 0 dB SNR.
Original languageEnglish (US)
Title of host publicationProceedings of 2010 IEEE International Symposium on Circuits and Systems
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages3533-3536
Number of pages4
ISBN (Print)9781424453085
DOIs
StatePublished - Aug 9 2010

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