IDENTIFICATION OF FIFTH-ORDER BLOCK-STRUCTURED NONLINEAR CHANNELS USING I.I.D. INPUT SIGNALS

This paper is concerned with the problem of nonlinear Wiener chan-nel identification using input-output crossmoments. The static non-linearity is assumed to be represented by a fifth-degree polynomial. For an i.i.d. input signal, we first derive closed-form expressions for estimating the second-order kernel of the associated fifth-order Volterra model. The parameters of the linear part of the fifth-order Wiener channel are then estimated using an eigenvalue decomposi-tion of the associated second-order Volterra kernel, while the non-linear subsystem is estimated in the least square sense from the re-constructed output of the linear subsystem. The proposed identifi-cation method is illustrated by means of simulation results. 1