Adaptive wavelets neural networks based multiuser detector

被引：0

作者：

Wang, L ^{[1
]}

Tao, HH ^{[1
]}

Jiao, LC ^{[1
]}

Liu, F ^{[1
]}

机构：

[1] Xidian Univ, Key Lab Radar Signal Proc, Xian 710071, Peoples R China

来源：

ICCIMA 2003: FIFTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, PROCEEDINGS | 2003年

关键词：

DS-CDMA; multiuser detection; matched filter; multiple access interference; adaptive wavelets neural networks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The capacity and performance of Code division multiple access(CDMA) system are limited by multiple access interference (MAI) and "near-far" problem,the effect on receivers of which depends on the users' signatures and the actual detector in the receiver. A adaptive wavelets neural networks (AWNN) based multiuser detector is proposed for demodulation of direct sequence CDMA(DS-CDMA) signals in both synchronous and asynchronous Gaussian channels, the complexity of which only lies on that of AWNN. The performance analysis of the detector are carried out by Monte Carlo simulations. The results show it greatly exceeds the matched filter detector and the multiplayer perceptron based multiuser detector. In addition,it approaches to the matched filters under single user scenario.

引用

页码：451 / 456

页数：6

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