期刊文献+

DS-CDMA中基于噪声独立分量分析的多用户检测

The Multi-user Detection Based on Noise Independent Component Analysis
下载PDF
导出
摘要 针对独立分量分析算法忽略噪声这一缺点,将基于噪声模型的噪声独立分量分析引入,并进行分析,得到基于噪声独立分量分析的多用户检测方法。并与基于无噪模型的独立分量分析算法的多用户检测性能进行仿真比较,结果表明本文引入的方法检测性能更优。 In order to remove the bias,we introduce a noise ICA algorithm based on the noise model and deduce the multi-user detection method based on this algorithm.To compare the performance of the two kinds of multi-user detection methods which are based on the normal ICA algorithm and the noise ICA algorithm,we simulate the two methods.Simulation results indicate that noise ICA algorithm method has better performance.
出处 《合肥师范学院学报》 2013年第3期27-29,共3页 Journal of Hefei Normal University
基金 合肥师范学院院级一般项目:2011kj04 安徽高校省级科学研究项目:KJ2012B142
关键词 噪声独立分量分析 快速定点ICA算法 多用户检测 noise ICA fast ICA algorithm multi-user detection
  • 相关文献

参考文献7

  • 1Liu Xiaozhi,Han Ying. Multi-user detection of DS—CDMAbased on noise~ ICA [C]. IEEE, 2010, 2: V2 — 177 — V2— 180. 被引量:1
  • 2Gupta M, Santhanam B. Prior ICA based blind multiuser de-tection in DS — CDMA systems [J]. Signals, Systems andComputers [J]. IEEE, 2004,2:2155-2159. 被引量:1
  • 3Aapo Hyvarinen, Juha Karhunen, Erkki Oja. IndependentComponent Analysis[M]. New York. John Wiley Sons,Inc. 2001. 被引量:1
  • 4Jyrki Joutsensalo and Tapani Ristaniemi. Learning Algorithmsfor blind Multiuser Detection in CDMA Downlink [I]. IEEE,? 1998,3:1040-1044. 被引量:1
  • 5Ristaniemi T,Joutsensalo J. Independent component analysiswith code information utilization in DS—CDMA signal separa-tion[J]. IEEE,1999,1 A:320-324. 被引量:1
  • 6Hyvarinen A, Oja E. Independent Component Analysis: Al-gorithms and Applications [J]. Neural Network, 2000, 13⑷:411-430. 被引量:1
  • 7Ekici O,Yongacoglu A, Application of noisy — independentcomponent analysis for CDMA signal separation [J]. IEEE,2004,5:3812-3816. 被引量:1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部