Blind identification of nonlinear FIR Volterra channels

The Volterra series has been successfully applied to a wide variety of engineering problems, such as modeling nonlinear communication channels, magnetic recording channels and physiological processes. In these engineering: designs, identification and equalization, especially, blind identification and equalization are very important. Although a nonlinear blind equalization approach is presented, this is an deterministic approach which works well only in the case of high SNR. In this paper, a subspace approach for blind identification and equalization of nonlinear single-input multiple-output (SIMO) FIR Volterra system is proposed. The approach only requires that the auto-correlation matrix of input signal is nonsingular. it can work well in the case of low SNR in comparison with the deterministic approach.