Decomposed Vector Rotation Model Sizing by Hill-Climbing Heuristic for Digital Predistortion of RF Power Amplifiers

Abstract

The decomposed vector rotation (DVR) model is proposed for digital predistortion (DPD) to compensate for the nonlinearities and memory effects of Power Amplifiers (PA). In this paper, we propose a new neighborhood definition for the DVR model that allows to extend the hill climbing (HC) algorithm to find the optimal structure of DVR model which provides the best compromise between modeling accuracy and complexity. The convergence of the algorithm has been verified and validated using real measurements from Class-AB PA.