Noise Characterisitcs Of Power Line Channel Based On High-Order Statistics

Power Line Communication(PLC)is a communication method that uses power lines as a transmission medium and is mainly used to transmit data,voice and video.This paper analyzes three kinds of noise,colored background noise,impulse noise and narrowband noise,which are common in power line channel,and then the paper uses Matlab to model three kinds of noise.Next,the characteristics of the power line channel are studied,and the power line channel is modeled.Three kinds of power line noise are added to the channel.In the power line communication model,the following three aspects of simulation experiments are carried out.Firstly,since the high-order cumulant can reflect the phase information of the signal,it can solve the defect that the second-order cumulant cannot realize the phase information detection.In this paper,the effect of fourth-order cumulant algorithm and second-order cumulant algorithm on signal-to-noise separation under different SNR conditions is studied.Secondly,the signal-to-noise ratio is very important in the processing of communication signals,and it also plays a key role in communication systems such as satellite communication and cellular communication.In this paper,we study the performance of three estimation algorithms,M2M4 estimation method,maximum likelihood estimation method and error vector amplitude method,under different signal-to-noise ratios.Finally,adaptive filtering is a filtering method based on linear filtering such as Wiener filtering.Because its filtering performance is stronger than the traditional filtering method,it has been widely used in practical engineering.The theoretical system,model and implementation steps of the adaptive algorithm are analyzed in detail.The recursive minimum quadratic algorithm and the third-order cumulant-based RLS algorithm are compared and the conclusions are drawn based on the simulation results.