Lattice-Reduction-Aided Sphere Decoding for MIMO Detection Achieving ML Performance

We propose a lattice-reduction-aided sphere decoding (SD) algorithm for MIMO detection achieving exact maximum likelihood (ML) detection performance with very low computational complexity in the mid and high signal-to-noise ratio (SNR) regions. A simple criterion is presented to determine if the ML...

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Bibliographic Details
Published inIEEE communications letters Vol. 20; no. 1; pp. 125 - 128
Main Authors Liu, Jinzhu, Xing, Song, Shen, Lianfeng
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Complexity
Computation
Computational complexity
Computer simulation
Criteria
Decoding
Lattice reduction
Lattices
Maximum likelihood decoding
maximum likelihood detection
MIMO
Searching
Signal to noise ratio
sphere decoding
maximum likelihood detection
sphere decoding
MIMO
Lattice reduction
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Summary:We propose a lattice-reduction-aided sphere decoding (SD) algorithm for MIMO detection achieving exact maximum likelihood (ML) detection performance with very low computational complexity in the mid and high signal-to-noise ratio (SNR) regions. A simple criterion is presented to determine if the ML detection result is obtained by a primary search. If not, a further search will be carried out to find the ML detection result eventually. Simulation results show that in the mid and high SNR environments, the computational complexity of the proposed algorithm is considerably lower than that of the conventional SD.
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ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2015.2504094