Low Complexity Adaptive Model for Digital Predistortion of RF Power Amplifiers in Time-Varying Configurations

DOI number:10.1109/TMTT.2022.3224192

Affiliation of Author(s):中国科技大学电子工程与信息科学系

Journal:IEEE Transactions on Microwave Theory and Techniques

Key Words:Decision tree, digital predistortion (DPD), greedy algorithm, piecewise model, power amplifiers (PAs), running complexity, time-varying configurations.

Abstract:A novel behavioral modeling approach called adaptive model tree (AMT) is proposed for digital predistortion
(DPD) of RF power amplifiers (PAs) in fixed and time-varying
configurations. The AMT model is piecewise based on the decision
tree and the reduced-complexity full basis-propagating selection
(RC-FBPS) model. A novel two-step joint iterative algorithm is
proposed to achieve a good match between the decision tree
and the submodels obtained from the RC-FBPS model. The
AMT model inherits and enhances the respective advantages
of the decision tree and RC-FBPS model to have a powerful
adaptive capability potentially. The experimental tests on a
Doherty PA confirm that the AMT model can achieve a better
trade-off between linearization performance and complexity than
the state-of-the-art model in the fixed configuration. Furthermore, to characterize and compensate for the complex dynamic
nonlinear distortions of PAs in time-varying configurations, the
piecewise modeling technique in time-varying configurations is
proposed and applied to the AMT model in this article. The
experimental results confirm that the AMT model achieves
excellent linearization performance with very low complexity in
time-varying configurations and good generalization performance
for new configuration combinations that are not used for training.

First Author:Renlong Han (韩仁龙)

Co-author:Wen Qiao,Chengye Jiang,Guichen Yang,Jingchao Tan

Indexed by:Journal paper

Correspondence Author:Falin Liu

Document Code:10.1109/TMTT.2022.3224192

Discipline:Engineering

Document Type:J

Volume:71

Issue:5

Page Number:2004-2015

Date of Publication:2023-05-06

Included Journals:EI、SCI