Optimization of digital predistortion models for RF power amplifiers using a modified differential evolution algorithm

Abstract

This paper, investigates and presents the optimal parameter identification of digital pre-distortion (DPD) models for radio frequency power amplifiers (RF PAs) using a modified differential evolution (MDE) based optimization algorithm. Compared to the conventional exhaustive search method which is computationally intensive, our proposed approach enables the identification of a best-fit DPD model from a combinatorially large model space in a short time. In addition, applying information criteria based objective functions in the optimization process enables us to achieve sparse selection of dynamical models, which balances the model accuracy and model complexity. Experimental validation on a GaN based class AB power amplifier illustrates that, our proposed approach was able to accurately identify complexity reduced optimal DPD models without compromising the modeling accuracy.