Threshold Optimized CSWPL Behavioral Model for RF Power Transistors Based on Particle Swarm Algorithm

被引：1

作者：

Liu, Bo ^{[1
]}

Guo, Jia ^{[1
]}

Tang, Xiaoqiang ^{[1
]}

Crupi, Giovanni ^{[2
]}

Cai, Jialin ^{[1
]}

机构：

[1] Hangzhou Dianzi Univ, Key Lab RF Circuit & Syst, Minist Educ, Hangzhou 310018, Peoples R China

[2] Univ Messina, BIOMORF Dept, I-98125 Messina, Italy

来源：

IEEE MICROWAVE AND WIRELESS TECHNOLOGY LETTERS | 2023年 / 33卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Behavioral sciences; Optimization; Predictive models; Radio frequency; Integrated circuit modeling; Adaptation models; Wireless communication; Canonical section-wise piecewise linear (CSWPL) function; nonlinear behavioral model; particle swarm optimization (PSO); power transistor; threshold optimization; HEMTS;

D O I：

10.1109/LMWT.2022.3226450

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this letter, the particle swarm optimization (PSO) is employed to optimize the threshold values of the canonical section-wise piecewise linear (CSWPL) function-based behavioral model of power transistors. The effectiveness of the proposed method is validated through measurements carried out on a 10-W GaN power transistor produced by Wolfspeed. Compared with the existing simultaneous perturbation stochastic approximation (SPSA) method, the developed modeling technique not only provides superior prediction performance across different input power levels but also finds the optimal thresholds much more efficiently.

引用

页码：531 / 534

页数：4

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