A Grouped-Iterative Framework for MIMO Detection

In this paper, we propose one grouped-iterative framework to generate a family of the MIMO detection algorithms. The presented framework not only includes the conventional iterative, grouped, and Chase detection algorithms, but also derives a new low-complexity MIMO detection algorithm. The proposed...

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Bibliographic Details
Published in2008 IEEE 68th Vehicular Technology Conference pp. 1 - 5
Main Authors Di-You Wu, Lan-Da Van
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2008
Subjects
Artificial neural networks
Bit error rate
Complexity theory
Detection algorithms
Detectors
Iterative algorithm
MIMO
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Summary:In this paper, we propose one grouped-iterative framework to generate a family of the MIMO detection algorithms. The presented framework not only includes the conventional iterative, grouped, and Chase detection algorithms, but also derives a new low-complexity MIMO detection algorithm. The proposed detection can adjust some parameters to achieve a range of trade-offs between performance and complexity. In (4,4) system with uncoded 16-QAM inputs, one instance of the proposed detection algorithm not only substantially reduces the multiplication complexity by 26.3% but also outperforms the BODF algorithm about 5 dB. Another instance of the proposed algorithm can save multiplication complexity by 34% at the penalty of 1 dB loss compared with the B-Chase detector.
ISBN:142441721X
9781424417216
ISSN:1090-3038
2577-2465
DOI:10.1109/VETECF.2008.123