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A novel nonlinear large‐signal statistical model of GaN HEMT used in S‐band power amplifier design and yield estimation
Author(s) -
Chen Zhikai,
Xu Yuehang,
Wang Changsi,
Wen Zhang,
Rong Chuicai,
Xu Ruimin
Publication year - 2016
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.2165
Subject(s) - high electron mobility transistor , amplifier , electronic engineering , transistor , large signal model , statistical model , power (physics) , nonlinear system , transistor model , computer science , signal (programming language) , engineering , electrical engineering , voltage , physics , artificial intelligence , cmos , quantum mechanics , programming language
Summary A novel GaN high‐electron mobility transistor (HEMT) nonlinear large‐signal statistical model based on empirical equivalent circuit is proposed in this paper. Thirty‐four GaN HEMTs from 10 batches are measured, and all the parameters of the large‐signal model are extracted by in‐house parameter extraction program. We choose six most sensitive parameters of the drain‐source current model and the gate charge model. The statistical method is modeled by using a symbolic processing method to change the range of the six parameters. The statistical model is implemented in Agilent ADS software for validation. A S‐band GaN HEMT power amplifier is designed by using the established statistical model for demonstration purpose. The results show that good accuracy has been achieved by comparing measured and simulated output power (Pout) and power added efficiency (PAE). So it has been proven that this method is suitable for GaN HEMT power amplifier design and yield estimation. Copyright © 2016 John Wiley & Sons, Ltd.