Adaptive predistortion of IIR Hammerstein systems using the Nonlinear Filtered-x LMS algorithm

Adaptive predistortion of nonlinear systems described using IIR Hammerstein models is introduced in this paper. The adaptive predistorter is modeled as an IIR Wiener system. The parameters of the linear and nonlinear blocks of the predistorter are estimated simultaneously using the nonlinear filtered-x least mean squares (NFxLMS) algorithm. The NFxLMS algorithm is derived under the assumption that the parameters of the IIR Wiener predistorter are changing slowly during adaptation. Simulation study shows that the suggested predistorter using the NFxLMS algorithm can well compensate the nonlinear distortion of the IIR Hammerstein system.