Impulse Noise Suppression Based on Power Iterative ICA in Power Line Communication

• Autorzy: Zhang Wei , Luo Zhongqiang , Xiong Xingzhong

Identyfikatory

DOI

10.24425/ijet.2019.129824

• Języki publikacji: EN

Abstrakty

EN

To overcome the detrimental influence of impulse noise in power line communication and the trap of scarce prior information in traditional noise suppression schemes , a power iteration based fast independent component analysis (PowerICA) based noise suppression scheme is designed in this paper. Firstly, the pseudo-observation signal is constructed by weighted processing so that single-channel blind separation model is transformed into the multi-channel observed model. Then the proposed blind separation algorithm is used to separate noise and source signals. Finally, the effectiveness of the proposed algorithm is verified by experiment simulation. Experiment results show that the proposed algorithm has better separation effect, more stable separation and less implementation time than that of FastICA algorithm, which also improves the real-time performance of communication signal processing.

Słowa kluczowe

EN

power line communication; PLC; orthogonal frequency division multiplexing signal; OFDM; independent component analysis; ICA; impulse noise

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2019
• Tom: Vol. 65, No. 4
• Strony: 651--656
• Opis fizyczny: Bibliogr. 25 poz., rys., wykr.

Twórcy

autor

Zhang Wei

• Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Yibin 644000, China

autor

Luo Zhongqiang

• Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Yibin 644000, China

autor

Xiong Xingzhong

• Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Yibin 644000, China

Bibliografia

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Uwagi

This work was supported by National Natural Science Foundation of China (No. 61801319), the Opening Project of Key Laboratory of Higher Education of Sichuan Province for Enterprise Informationalization and Internet of Things (No. 2017WZJ01), Sichuan University of Science and Engineering Talent Introduction Project (No.2017RCL11), the Education Agency Project of Sichuan Province (No.18ZB0419), and the Major Frontier Project of Science and Technology Plan of Sichuan Province (No. 2018JY0512), and the Sichuan Institute of Technology Graduate Innovation Foundation (No. Y2018038).