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 a 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 the input signal is nonsingular. It can work well in the case of low SNR in comparison with the deterministic approach