DocumentCode :
1932051
Title :
Step-Down Grouping Maximization-Likelihood Algorithms and its Application in DS-CDMA System
Author :
Wang, Lei ; Li, Lei
Author_Institution :
Nanjing Univ. of Posts & Telecommun., Nanjing
Volume :
4
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
2421
Lastpage :
2426
Abstract :
We focus on the maximization-likelihood algorithms and its application aimed at achieving satisfactory performance at the price of a moderate computational complexity. We propose a new algorithm named step-down grouping maximization likelihood (SGML). At the analysis stage, some interesting properties shared by the proposed procedures are proven. Finally, the performance assessment shows that the new schemes are superior to the linear detectors in DS-CDMA system, and some of them achieve a bit-error rate close to that of the optimum receiver.
Keywords :
code division multiple access; communication complexity; maximum likelihood detection; DS-CDMA system; computational complexity; step-down grouping maximization-likelihood algorithms; Computational complexity; Cybernetics; Detectors; Iterative algorithms; Machine learning; Machine learning algorithms; Multiaccess communication; Multiple access interference; Multiuser detection; SGML; Direct-sequence code-division multiple-access (DS-CDMA) systems; Iterative detection; Maximization likelihood; Multi-user detection; Step-down grouping maximization likelihood (SGML);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370551
Filename :
4370551
Link To Document :
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