自动加的夫模型复杂性识别和参数提取从测量定制a -拉数据

IF 4.9 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Azam Al-Rawachy;Alexander Baddeley;Abdalla Eblabla;Dragan Gecan;Aamir Sheikh;Aleksander Bogusz;Roberto Quaglia;Paul J. Tasker
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引用次数: 0

摘要

本文提出了一种新的实验技术,用于使用传统的窄带有源负载-拉系统自动识别微波晶体管卡迪夫行为模型的复杂性和系数。该方法保证了提取模型的准确性,同时消除了专家判断/干预的需要。本文详细介绍了采用基于窄带矢量网络分析仪的负载-拉系统来克服实现a -拉的技术挑战所采用的解决方案。具体来说,要确保快速准确地实现a -拉网格,并为被测设备提供有意义且安全的操作空间。对氮化镓(GaN)微波晶体管进行了表征和建模,并在2.45 GHz频段演示了该技术。结果清楚地显示了如何自动识别模型复杂性并提取准确的系数。此外,本文还演示了如何使用这种方法在不影响模型精度的情况下系统地减少测量负载点的数量,从而进一步提高过程的速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Cardiff Model Complexity Identification and Parameters Extraction From Measured Tailored A-Pull Data
This paper presents a novel experimental technique for automatically identifying the complexity and coefficients of a Cardiff behavioral model of a microwave transistor using a conventional, narrowband active load-pull system. The method ensures the accuracy of the extracted model while eliminating the need for expert human judgment/intervention. The paper details the solutions adopted to overcome the technical challenges of implementing A-pull using a narrowband vector network analyzer-based load-pull system. Specifically, to ensure that the A-pull grid is achieved quickly and accurately, and that it covers a meaningful and safe operating space for the device under test. A gallium nitride (GaN) microwave transistor is characterized and modeled to demonstrate the technique at 2.45 GHz. Results clearly show how the model complexity is automatically identified and accurate coefficients extracted. In addition, the paper demonstrates how to use this approach to allow for a systematic reduction in the number of measured load points without compromising model accuracy, further improving the process’s speed.
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来源期刊
CiteScore
10.70
自引率
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审稿时长
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