Average filtered blind separation of DS-CDMA signals with ICA method

Miao Yu, Jianzhong Chen, Shiju Li
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引用次数: 2

Abstract

In DS-CDMA system, the pseudo random sequences are none correlation and the information sequences of different user's are independent, thus Independent Component Analysis (ICA) is appropriate for the blind separate the DS-CDMA signals with little prior knowledge. Original blind separation method of DS-CDMA signals with ICA utilized only one sample value in each chip. However, in common DS-CDMA communication systems, the sample rate is much faster than the chip rate, so there are many samples during a chip interval. A method of average filtered blind separation of DS-CDMA signals with ICA is proposed in this paper. When noise is stationary, the method proposed could increase the input SNR of ICA greatly. The validity of the method is proved by the simulation results at last.
DS-CDMA信号的ICA平均滤波盲分离
在DS-CDMA系统中,由于伪随机序列不相关,而不同用户的信息序列是独立的,因此独立分量分析(ICA)适合于在缺乏先验知识的情况下对DS-CDMA信号进行盲分离。原始的基于ICA的DS-CDMA信号盲分离方法在每个芯片中只利用了一个采样值。然而,在普通的DS-CDMA通信系统中,采样率比芯片速率快得多,因此在一个芯片间隔内会有很多采样。提出了一种利用ICA对DS-CDMA信号进行平均滤波盲分离的方法。在噪声平稳的情况下,该方法可以大大提高ICA的输入信噪比。最后通过仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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