Fast Independent Component Analysis Based Digital Modulation Recognition Method
This paper proposes an efficient Independent Component Analysis (ICA) based modulation feature extraction method applied in digital modulation identification. In modulation identification, important information may be contained in the highorder relationship among sampling points. ICA is sensitive to high-order statistic in the data and finds not-necessarily orthogonal bases, so it may better identify and reconstruct high-dimensional communication signal data than traditional time and frequency domain features. ICA algorithms are timeconsuming and sometimes converge difficultly. So a modified FastICA algorithm is developed in this paper, which only need to computer Jacobian Matrix once time in one iteration and achieves the correspondent effect of FastICA. After obtaining all independent components, a genetic algorithm is introduced to select optimal independent components (ICs). The experiment results show that modified FastICA algorithm fast convergence speed and genetic algorithm optimize recognition performance. ICA based features extraction method is innovative and promising for digital modulation identification.
Independent Component Analysis modulation recognition Jacobian Matriz feature eztraction
Yiqiong Xu Lindong Ge Bo Wang
National Digital Switching System Engineering and Technology Research Center Zhenzhou, China National Digital Switching System Engineering and Technology Research Center Zhenzhou,China
国际会议
The International Conference on Communication Software and Networks(2009 IEEE通信软件与网络国际会议 ICCSN 2009)
成都
英文
704-707
2009-02-20（万方平台首次上网日期，不代表论文的发表时间）