Digital predistortion for power amplifiers using separable functions

TL;DR

This paper develops a theoretical framework and a systematic structure for digital predistortion of RF power amplifiers, using separable functions to improve linearization without relying on specific HPA models.

Contribution

It introduces a general predistorter structure based on separable functions, avoiding traditional model assumptions and establishing the equivalence of predistorters and postdistorters.

Findings

Theoretical proof of predistorter and postdistorter equivalence.

A systematic predistorter design using separable functions.

Enhanced linearization of HPAs without specific model assumptions.

Abstract

This paper is concerned with digital predistortion for linearization of RF high power amplifiers (HPAs). It has two objectives. First, we establish a theoretical framework for a generic predistorter system, and show that if a postdistorter exists, then it is also a predistorter, and therefore, the predistorter and postdistorter are equivalent. This justifies the indirect learning methods for a large class of HPAs. Secondly, we establish a systematic and general structure for a predistorter that is capable of compensating nonlinearity for a large variety of HPAs. This systematic structure is derived using approximation by separable functions, and avoids selection of predistorters based on the assumption of HPA models traditionally done in the literature.