Reduced complexity list sphere decoding for MIMO systems

Depth-first sphere decoding of MIMO systems has near maximum likelihood performance with reasonable computational complexity. In this paper, lower complexity depth-first sphere decoding and list sphere decoding algorithms are proposed. Several criteria for re-ordering the search dimensions are propo...

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Bibliographic Details
Published in:Digital signal processing 2014-02, Vol.25, p.84-92
Main Authors: El-Khamy, Mostafa, Medra, Mostafa, ElKamchouchi, Hassan M.
Format: Article
Language:English
Subjects:
Algorithms
Cancellation
Complexity
Criteria
Decoders
Decoding
Depth-first search
Interference cancellation
List decoding
Lists
MIMO
Reduction
Sphere decoding
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Summary:Depth-first sphere decoding of MIMO systems has near maximum likelihood performance with reasonable computational complexity. In this paper, lower complexity depth-first sphere decoding and list sphere decoding algorithms are proposed. Several criteria for re-ordering the search dimensions are proposed. The proposed sphere decoders are shown to have a significantly reduced decoding complexity at low SNRs. To further reduce the complexity at high SNRs, the point search-space at each ordered dimension is adaptively reduced. Further reductions in the decoding complexity are achieved by inter-layer interference cancellation. It is shown that the proposed sphere decoding algorithms maintain their near-optimal performance, concurrently with a significant complexity reduction, over a wide SNR range.
ISSN:1051-2004
1095-4333
DOI:10.1016/j.dsp.2013.10.023