Digital Predistortion Using Adaptive Basis Functions

This paper is concerned with digital predistortion (DPD) for linearization of radio frequency (RF) high power amplifiers (PAs). We propose an adaptive scheme for selecting basis functions for both direct and indirect learning digital predistortion architectures. The adaptive scheme has the advantage of reducing the complexity and, at the same time, increasing the convergence rate and stability of digital predistortion. Simulation and lab experimental results are presented to demonstrate the effectiveness of using adaptive basis functions in a hardware platform with a solid state high power amplifier. Index Terms-- digital predistortion, power amplifier linearization, predistorter, direct learning, indirect learning, stability of digital predistortion adaptive selection of basis functions.