Sparse Model Selection of Digital Predistorters Using Subspace Pursuit

Abstract

This communication presents a new technique for the digital predistortion of power amplifiers (PAs) based on sparse behavioral models. The subspace pursuit algorithm formulation is adapted to work in the nonlinear series framework. Experiments driven on a test bench based on a GaN PA driven by a 15-MHz filter bank multicarrier (FBM C) signal were conducted in order to validate the algorithm. Experimental results in a digital predistortion scenario and the comparison with the orthogonal matching pursuit highlight the enhancement of this pruning method.