DocumentCode :
1371860
Title :
A Fixed-Complexity Smart Candidate Adding Algorithm for Soft-Output MIMO Detection
Author :
Milliner, David L. ; Zimmermann, Ernesto ; Barry, John R. ; Fettweis, Gerhard
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
3
Issue :
6
fYear :
2009
Firstpage :
1016
Lastpage :
1025
Abstract :
We present a soft-output multiple-input multiple-output (MIMO) detection algorithm that achieves near max-log optimal error rate performance with low- and fixed-computational complexity. The proposed smart ordering and candidate adding (SOCA) algorithm combines a smart-ordered QR decomposition with smart candidate adding and a parallel layer-by-layer search of the detection tree. In contrast to prior algorithms that use smart candidate adding, the proposed algorithm has fixed computational complexity, and it never visits a node more than once. Results indicate that the SOCA algorithm has an attractive performance-complexity profile for both fast and slow fading 4 × 4 and 8 × 8 MIMO channels with quadrature amplitude modulation (QAM) inputs.
Keywords :
MIMO communication; error statistics; quadrature amplitude modulation; signal detection; tree searching; MIMO channels; detection tree; fixed-complexity smart candidate adding algorithm; list detection; max-log optimal error rate performance; performance-complexity profile; quadrature amplitude modulation; smart ordering and candidate adding; soft-output MIMO detection; Amplitude modulation; Computational complexity; Decoding; Detection algorithms; Detectors; Error analysis; Fading; MIMO; Power system reliability; Signal processing algorithms; Breadth-first; list detection; parallel smart candidate adding; smart ordering and candidate adding (SOCA); smart-ordered QR; soft-output multiple-input multiple-output (MIMO) detection; tree search;
fLanguage :
English
Journal_Title :
Selected Topics in Signal Processing, IEEE Journal of
Publisher :
ieee
ISSN :
1932-4553
Type :
jour
DOI :
10.1109/JSTSP.2009.2035800
Filename :
5370672
Link To Document :
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