多目标粒子群自动优化法用于有效设计 Doherty 功率放大器

IF 1.6 4区工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Numerical Modelling-Electronic Networks Devices and Fields Pub Date : 2024-01-11 DOI:10.1002/jnm.3204

Zefang Hao, Yan Qu, Jiajun Huang, Giovanni Crupi, Jialin Cai

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引用次数: 0

摘要

本文针对多尔蒂功率放大器（DPA）的设计开发了一种自动多目标粒子群优化（AMOPSO）方法。与商业模拟器中众所周知的内置优化器相比，所提出的方法不仅缩短了优化时间，还为最终功率放大器提供了出色的功率附加效率（PAE）。根据所报告的测量结果，在 6 dB 回退时，所制造 DPA 的输出 PAE 超过 50%，饱和 PAE 超过 61%，在 1.9-2.1 GHz 目标频率范围内，饱和输出功率 (Pout) 超过 43 dBm。与现有的优化方法相比，所提出的方法可将优化时间缩短 37% 以上。

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Automatic multi-objective particle swarm optimization method for effective Doherty power amplifier design

In this paper, an automatic multi-objective particle swarm optimization (AMOPSO) method is developed for the design of Doherty power amplifiers (DPAs). In comparison to the well-known built-in optimizer available in commercial simulators, the proposed method not only reduces the optimization time, but also provides superior power added efficiency (PAE) for the final power amplifier. According to the reported measurements, the output PAE of the fabricated DPA exceeds 50% at 6 dB backoff, the saturated PAE is more than 61%, and the saturated output power (Pout) is over 43 dBm in the target frequency range of 1.9–2.1 GHz. As compared with existing optimization methods, the proposed method allows reducing optimization time by more than 37%.

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来源期刊

International Journal of Numerical Modelling-Electronic Networks Devices and Fields 工程技术-工程：电子与电气

CiteScore

4.60

自引率

6.20%

发文量

101

审稿时长

>12 weeks

期刊介绍： Prediction through modelling forms the basis of engineering design. The computational power at the fingertips of the professional engineer is increasing enormously and techniques for computer simulation are changing rapidly. Engineers need models which relate to their design area and which are adaptable to new design concepts. They also need efficient and friendly ways of presenting, viewing and transmitting the data associated with their models. The International Journal of Numerical Modelling: Electronic Networks, Devices and Fields provides a communication vehicle for numerical modelling methods and data preparation methods associated with electrical and electronic circuits and fields. It concentrates on numerical modelling rather than abstract numerical mathematics. Contributions on numerical modelling will cover the entire subject of electrical and electronic engineering. They will range from electrical distribution networks to integrated circuits on VLSI design, and from static electric and magnetic fields through microwaves to optical design. They will also include the use of electrical networks as a modelling medium.