In order to enhance the ability of multiple-input multiple-output (MIMO) power line communication system against the impulsive noise

a scheme is proposed to mitigating the impulsive noise impact on MIMO power line communications based on sparse Bayesian learning and correlation of impulsive noise on power lines. Under this scheme

all of the subcarriers are used to jointly estimate the impulsive noise and the signals on the available subcarriers. There is no need for information of training impulsive noise. The Bivariate Middleton Class A model is used in the case study to fit the impulsive noise

and the results show that the performance of the proposed scheme against the impulsive noise is better than the multiple measurement vector sparse Bayesion learning (MSBL) scheme using null subcarriers with an improvement of 11 dB signal to noise ratio (SNR).