DocumentCode :
3642948
Title :
Soft-output sphere decoding: Single tree search vs. improved k-best
Author :
Martin Mayer;Michal Šimko;Markus Rupp
Author_Institution :
Institute of Telecommunications, Vienna University of Technology, Austria, Gusshausstrasse 25/389, A-1040 Vienna, Austria
fYear :
2011
fDate :
6/1/2011 12:00:00 AM
Firstpage :
1
Lastpage :
4
Abstract :
Multiple-Input Multiple-Output systems provide high multiplexing gain for digital transmissions. However, this is only achievable if an expedient detection method is used. A common method is Maximum Likelihood (ML) detection which enables soft decisions for each received bit along with good error performance. The drawback of this method is its demanding algorithm. In order to meet real-time constraints, the ML detection can be approximated. In this paper, we compare three different implementations of the soft sphere decoder: the single tree search which achieves true ML performance, a conventional k-best algorithm that delivers approximated ML detection, and a novel improved k-best algorithm with better ML approximation at cost of slightly increased execution time. We examine different performance aspects of these sphere decoder implementations and give a recommended complexity-border which indicates where the usage of an ML approximation becomes appropriate.
Keywords :
"Approximation methods","Maximum likelihood decoding","Signal to noise ratio","Antennas","Measurement","MIMO"
Publisher :
ieee
Conference_Titel :
Systems, Signals and Image Processing (IWSSIP), 2011 18th International Conference on
ISSN :
2157-8672
Print_ISBN :
978-1-4577-0074-3
Electronic_ISBN :
2157-8702
Type :
conf
Filename :
5977346
Link To Document :
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