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