Blind two-input-two-output FIR channel identification based on frequency domain second- order statistics

We present an analytical solution to the two-input-two-output blind crosswi se mixture identification based on eigenvalue decomposition of second-order spectra correlations. The sources are independent and nonwhite, but otherw ise, we consider their statistics to be unknown. We show that the cross cha nnels cannot be uniquely determined by the analysis of the frequency domain covariance alone due to the unknown eigenvector permutations. However, the problem can be attacked with the help of two invariant indices that are im mune to these permutations. Using these indices together with standard reco nstruction-from-phase techniques, we show that the channels can be uniquely determined, Our theoretical results lead to a novel frequency domain secon d-order algorithm that identifies the unknown channels.