An Ameliorated Small-Signal Model Parameter Extraction Method for GaN HEMTs up to 110 GHz with Short-Test Structure

IF 1.3 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Active and Passive Electronic Components Pub Date : 2023-11-21 DOI:10.1155/2023/5589831

Qingyu Yuan, Jinze Tang, Xiaodong Luan, Xin Lin, Fan Chang, Jiali Cheng

引用次数: 0

Abstract

An improved method of extracting small-signal equivalent circuit model parameters for gallium nitride high electron mobility transistors (GaN HEMTs) is presented. This paper intends to present a method to extract the parasitic inductance and resistance of transistors based on the short-test structure without the open-circuit test structure. The parasitic capacitance of transistors is extracted by the method based on the size scalable model. Compared with the traditional COLD-FET method, the extraction procedure is simpler and more convenient. After removing the influence of parasitic elements, the intrinsic parameters of the model can be extracted by the S-parameters measured at different bias points. The experimental results show that the simulation results have good agreement with the measured results in the range of 0.5∼110 GHz.

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一种改进型小信号模型参数提取方法，适用于频率高达 110 GHz 且具有短测试结构的 GaN HEMT

本文介绍了一种提取氮化镓高电子迁移率晶体管（GaN HEMT）小信号等效电路模型参数的改进方法。本文旨在介绍一种基于短路测试结构而非开路测试结构来提取晶体管寄生电感和电阻的方法。该方法基于尺寸可扩展模型提取晶体管的寄生电容。与传统的 COLD-FET 方法相比，提取过程更加简单方便。在消除寄生元件的影响后，可以通过在不同偏置点测量的 S 参数来提取模型的内在参数。实验结果表明，在 0.5∼110 GHz 范围内，仿真结果与测量结果具有良好的一致性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Active and Passive Electronic Components ENGINEERING, ELECTRICAL & ELECTRONIC-

CiteScore

1.30

自引率

0.00%

发文量

审稿时长

13 weeks

期刊介绍： Active and Passive Electronic Components is an international journal devoted to the science and technology of all types of electronic components. The journal publishes experimental and theoretical papers on topics such as transistors, hybrid circuits, integrated circuits, MicroElectroMechanical Systems (MEMS), sensors, high frequency devices and circuits, power devices and circuits, non-volatile memory technologies such as ferroelectric and phase transition memories, and nano electronics devices and circuits.