Support vector machine multiuser receiver for DS-CDMA signals in multipath channels
摘要：
The problem of constructing an adaptive multiuser detector (MUD) is considered for direct sequence code division multiple access (DS-CDMA) signals transmitted through multipath channels. The emerging learning technique, called support vector machines (SVM), is proposed as a method of obtaining a nonlinear MUD from a relatively small training data block. Computer simulation is used to study this SVM MUD, and the results show that it can closely match the performance of the optimal Bayesian one-shot detector. Comparisons with an adaptive radial basis function (RBF) MUD trained by an unsupervised clustering algorithm are discussed.
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关键词：
Theoretical or Mathematical/ code division multiple access learning automata multipath channels neural nets receivers spread spectrum communication/ support vector machine multiuser receiver DS-CDMA signals multipath channels adaptive multiuser detector MUD direct sequence code division multiple access signals emerging learning technique SVM optimal Bayesian one-shot detector adaptive radial basis function RBF unsupervised clustering algorithm/ B6150E Multiple access communication B6150M Protocols B6250 Radio links and equipment B6110 Information theory B1295 Neural nets (circuit implementations) C1290Z Other applications of systems theory C4220 Automata theory C1230D Neural nets C5290 Neural computing techniques
DOI：
10.1109/72.925563
被引量：
年份：
2001
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