On Segmented Predistortion for Linearization of RF Power Amplifiers

Abstract

This paper presents a general survey of digital predistortion (DPD) techniques with segmentation. A comparison of global DPD with two segmented approaches namely Vector-Switched DPD and Decomposed Vector Rotation DPD is presented with the support of experimentation on a strongly non-linear 3 ways Doherty PA. It shows the interest of both segmented approaches in terms of linearization performance, complexity and ease of implementation compared to the global DPD. The paper starts with some mathematical generalities on interpolation and splines. It focuses on segmented models derived from Volterra series even if the presented principles can also be applied to neural networks.

Characterization of RF Power Amplifier for Narrow and Wide Band Memory Polynomial Implementations

“…in [12] proposed an approach for ex-traction of digital predistorter model of RF power amplifiers utilizing only 1-bit resolution analog to digital converters in the observation path to deal with the error signal between input and output signals, the DPD coefficients were estimated then on the basis of direct learning architecture by using measured error signal. The digital predistortion techniques with segmentation were presented in [13] by doing comparative analysis of global DPD with two segmented approaches such as Vector-Switched DPD and Decomposed Vector Rotation DPD with the support of experimentation on a 3 ways Doherty Power Amplifier which is strongly non linear. A joint-polynominal LUT predistorter algorithm was proposed in [14] which offers a better rejection of error vector magnitude distortion and an improved adjacent channel leakage ratio upto 30-40% for wideband code division multiple access at minimum usage of memory.…”