Source Correlation Compensation for Blind Channel Identification Based on Second-Order Statistics

We present a source correlation compensation approach for the blind channel identification method recently proposed by Tong et al. [1]. Instead of assuming independent and identically distributed (i.i.d.) source symbols as assumed by Tong et al., we consider the case where each source symbol is weakly correlated to its nearest neighbors with an unknown correlation coefficient. We show how Tong's method can be simply modified so that the unknown correlation coefficient can be estimated and then compensated, which leads to an improved performance.