A semi-analytical method for blind separation of cyclostationary sources in digital communications

Amine Brahmi, H. Ghennioui, C. Corbier, M. Lahbabi, F. Guillet
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Abstract

This work puts forward the problem of blind mixing matrix identification in the case of linearly mixed signals of cyclostationay sources whose cyclic frequencies are unknown and different. The identification is achieved using a semi-analytical solution. It takes advantage of the Eigenvalue Decomposition (EVD) of a set of algebraically particular matrices resulted from the application of the cyclic autocorrelation function on the mixed signals and rank-one selection criteria combined with a hierarchical clustering method. The proposed approach is applied to digital communication signals then numerical simulations are provided to illustrate the proper behaviour of the proposed method in different noise contexts.
数字通信中循环平稳源盲分离的半解析方法
本文提出了循环频率未知且不同的循环平稳源线性混合信号的盲混合矩阵辨识问题。鉴定是使用半解析解实现的。它利用循环自相关函数在混合信号上应用所产生的一组代数特定矩阵的特征值分解(EVD)和秩一选择准则,并结合层次聚类方法。将所提出的方法应用于数字通信信号,并进行了数值模拟,以说明所提出的方法在不同噪声环境下的适当行为。
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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