An Enhanced Impulsive Noise Suppression Method Based on Wavelet Denoising and ICA for Power Line Communication

Abstract

Aiming at the problem of noise suppression in power lines, traditional noise suppression methods need to know prior knowledge and other defects. In this paper, blind source separation methods that do not need prior knowledge are selected. In the case of low signal-to-noise ratio, the basic independent component analysis algorithm has poor denoising effect. Therefore, this paper proposes a joint independent component analysis algorithm based on Wavelet denoising and Power independent component analysis (WD-PowerICA). In this work, firstly, the pseudo observation signal is constructed by weighted processing, and the blind separation model of single channel is transformed into a multi-channel determined model. Then, the proposed WD-PowerICA algorithm is used to separate noise and source signals. Finally, the simulation results demonstrate that the proposed algorithm in this paper can effectively separate noise and source signal under low SNR. At the same time, the stronger the α pulse noise is, the closer the WD-PowerICA separated signal is to the source signal. The proposed algorithm is better than the state of the art PowerICA algorithm.

A Time Domain Noise Measurement and Analysis for Broadband Indoor Power Line Communications

“…The impulsive noise seems to have the greatest impact on signal transmission. It is random in nature with large amplitude that interferes with PLC and hence, leads to an increase in bit error rate of signal transmission [6]. Noise in PLC is of different types depending on its source as well as its physical properties.…”

“…The average indoor power supply in Nigeria is 240V at 50Hz. The electrical power grid consists of high, medium and low voltage transmission respectively [5,6]. The broadband PLC system is divided into two categories: Indoor PLC and last mile PLC.…”