Digital predistortion of parallel Wiener-type systems using the RPEM and NFxLMS algorithms

This paper considers the problem of digital predistortion of parallel Wiener-type systems using the recursive prediction error method (RPEM) and the nonlinear filtered-x least mean squares (NFxLMS) algorithms. The RPEM algorithm is used for the identification of the parallel Wiener-type system and the FIR filter that represents the inverse of the linear kernels. Then the estimate of the nonlinear kernels and the inverse of the linear kernels are used to construct the predistorter as done in. On the other hand, the NFxLMS algorithm is used to directly estimate the coefficients of the predistorter modeled using Volterra series. A comparative simulation study between the two algorithms is given in this paper.