Joint-Encoding-Based Multimodel Optimization for Digital Predistortion of RF Power Amplifiers

DOI number:10.1109/TMTT.2026.3683474

Affiliation of Author(s):中国科学技术大学信息学院

Teaching and Research Group:电子工程与信息科学系

Journal:IEEE Transactions on Micriwave Theory and Techniques

Funded by:NFSC 62371436

Key Words:Behavioral modeling, digital predistortion(DPD), genetic algorithm (GA), joint optimization, power amplifier (PA).

Abstract:In digital predistortion (DPD) of power amplifiers(PAs), the intricate nonlinear characteristics of PAs make it a critical challenge to construct a high-performance basis function space and to design an efficient basis function search algorithm. To address this challenge, this article first introduces the threshold amplitude polynomial (TAP) model and formulates it within a novel genetic algorithm (GA)-based model encoding framework, in which the basis function structures of the TAP model are sequentially encoded through binary bits. Building upon this framework, a piecewise polynomial modeling-based cascaded encoding strategy is further introduced to enhance the flexibility of the DPD scheme, where all encoded basis functions from the multiple submodels are concatenated to form a unified cascade chromosome. Subsequently, a joint-encoding-based multimodel optimization (JEMO) method is proposed, which leverages the encoded basis function structures within submodels through iterative GA operations to provide feedback for adjusting segmentation boundaries, thereby tightly integrating adaptive segmentation rules with the structural optimization of multiple submodels. To validate the effectiveness of the proposed model, experiments are conducted on two different Doherty PAs. The results demonstrate that the proposed JEMO model exhibits a significant advantage over other models in achieving the tradeoff between performance and complexity.

First Author:Hao Chang (昌昊)

Co-author:Chengye Jiang,Junsen Wang,Qianqian Zhang,Renlong Hang

Indexed by:Journal paper

Correspondence Author:Falin Liu

Document Code:10.1109/TMTT.2026.3683474

Discipline:Engineering

Document Type:J

Volume:74

Issue:7

Page Number:5811-5825

Translation or Not:no

Date of Publication:2026-04-10