A Recursive Prediction Error algorithm for digital predistortion of FIR Wiener systems

This paper considers the problem of predistortion of nonlinear systems which are described using FIR Wiener models by connecting two adaptive FIR Hammerstein systems. The first adaptive Hammerstein system is a training filter connected in parallel with the nonlinear system and its coefficients are estimated recursively using the recursive prediction error method (RPEM) algorithm. The second adaptive Hammerstein system is a predistorter connected in tandem with the nonlinear system and its coefficients are a copy from the training Hammerstein system. Simulation results show that the suggested RPEM algorithm effectively reduces spectral regrowth due to nonlinear distortion.