Predistorter design employing parallel piecewise linear structure and inverse coordinate mapping for broadband communications

This paper proposes a low-complexity predistorter (PD) for compensation of both the AM/AM and the AM/PM conversions with memory. The nonlinear power amplifier (PA) is modeled as a Wiener type nonlinearity. The quasi-static nonlinearities are modeled using a class of piecewise linear (PWL) functions. The PWL function facilitates an efficient PD identification algorithm. The proposed algorithm involves a novel inverse coordinate mapping (ICM) method that maps the nonlinear characteristics of the PA to that of the PD, and parameter estimations that do not require matrix inversion. The indirect learning architecture is used to provide an on-line compensation of the memory effect of the PA. Simulation results show that the PD that compensates also the AM/PM distortion performs significantly better than one that considers only the AM/AM nonlinearity. The proposed PD is also shown to outperform the orthogonal polynomial PD in both adjacent channel interference suppression and in-band distortion compensation.