Enhanced Block-Oriented Behavioral Model for the Linearization of Nonlinear Power Amplifiers with Strong Memory Effects

This paper proposes a new behavioral model for the linearization of radio frequency (RF) power amplifiers (PAs) exhibiting strong nonlinear memory effects. The proposed model enhances the augmented Hammerstein model through the inclusion of cross-terms, and as a result, improved accuracy and linearization performance are achieved. This technique benefits from the advantages of block-based models and adds more robustness against strong nonlinear memory effects in wideband applications. A proof-of-concept prototype using a commercial PA was built in order to test and evaluate the linearization performance of the proposed DPD. The performance assessment was carried out using 5G new radio (NR) signals with a bandwidth of 40 MHz and a PAPR of 8 dB. The proposed predistorter showed better linearization performance compared to the conventional and augmented Hammerstein-based predistorters.