东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2012, Vol. 33 ›› Issue (6): 778-781.DOI: -

• 论著 • 上一篇    下一篇

基于核独立分量分析的盲多用户检测算法

刘晓志;冯大伟;杨英华;秦树凯;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(N100404018)

Blind multi-user detection algorithm based on kernel independent component analysis

Liu, Xiao-Zhi (1); Feng, Da-Wei (1); Yang, Ying-Hua (1); Qin, Shu-Kai (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Liu, X.-Z.
  • About author:-
  • Supported by:
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摘要： 针对DS-CDMA通信系统中的盲多用户检测问题,提出了一种改进的核独立分量分析(KICA)算法.该算法首先将五阶收敛的牛顿迭代公式引入到传统的FastICA算法中,同时还引入了一种新的核函数——混合核函数来解决非线性混合信号的分离问题,从而实现了多用户信号检测.最后将所提出的算法与传统的FastICA算法和KICA算法进行仿真比较.结果表明:所提出的算法不仅收敛速度较快,而且具有较小的误码率.

关键词: 核独立分量分析, 多用户检测, 牛顿迭代, 混合核函数, 多址干扰

Abstract: For the problem of blind multi-user detection in the DS-CDMA system, an improved kernel independent component analysis (KICA) algorithm was proposed. First, fifth-Newton iteration method was introduced to the traditional FastICA algorithm, and then, a new kernel function-hybrid kernel function was used to solve the separation of nonlinear mixed signals. Based on the proposed algorithm, the multi-user signal detection was realized. At last, the proposed algorithm was compared with the traditional FastICA and KICA algorithms, and the simulation results showed that the improved-KICA algorithm had the smaller bit error rate and good convergent speed.

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