Reliable Hybrid Small-Signal Modeling of GaN HEMTs Based on Particle-Swarm-Optimization

This paper presents an efficient parameter extraction method applied to GaN high electron mobility transistors. The procedure only relies on <inline-formula> <tex-math notation="LaTeX">{S} </tex-math></inline-formula>-parameter measurements at cold bias conditions t...

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Published in:	IEEE transactions on computer-aided design of integrated circuits and systems Vol. 37; no. 9; pp. 1816 - 1824
Main Authors:	Hussein, Ahmed S., Jarndal, Anwar H.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Capacitance Computer simulation Electron mobility Gallium nitride GaN high electron mobility transistor (HEMT) HEMTs High electron mobility transistors Mathematical models MODFETs Optimization Parameters parameters extraction Particle swarm optimization particle swarm optimization (PSO) Reliability Semiconductor devices small-signal modeling Solid modeling
ISSN:	0278-0070, 1937-4151
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Abstract	This paper presents an efficient parameter extraction method applied to GaN high electron mobility transistors. The procedure only relies on <inline-formula> <tex-math notation="LaTeX">{S} </tex-math></inline-formula>-parameter measurements at cold bias conditions to extract the extrinsic parameters of a 19-element small-signal model. Hybrid technique of particle-swarm-optimization and direct fitting has been developed and implemented. The extraction procedure has been optimized to consider measurements uncertainty and improve the reliability of the extraction. The procedure has been validated by multibias extraction for different device sizes. A very good agreement between simulations and measurements has been obtained.
AbstractList	This paper presents an efficient parameter extraction method applied to GaN high electron mobility transistors. The procedure only relies on <inline-formula> <tex-math notation="LaTeX">{S} </tex-math></inline-formula>-parameter measurements at cold bias conditions to extract the extrinsic parameters of a 19-element small-signal model. Hybrid technique of particle-swarm-optimization and direct fitting has been developed and implemented. The extraction procedure has been optimized to consider measurements uncertainty and improve the reliability of the extraction. The procedure has been validated by multibias extraction for different device sizes. A very good agreement between simulations and measurements has been obtained. This paper presents an efficient parameter extraction method applied to GaN high electron mobility transistors. The procedure only relies on [Formula Omitted]-parameter measurements at cold bias conditions to extract the extrinsic parameters of a 19-element small-signal model. Hybrid technique of particle-swarm-optimization and direct fitting has been developed and implemented. The extraction procedure has been optimized to consider measurements uncertainty and improve the reliability of the extraction. The procedure has been validated by multibias extraction for different device sizes. A very good agreement between simulations and measurements has been obtained.
Author	Hussein, Ahmed S. Jarndal, Anwar H.
Author_xml	– sequence: 1 givenname: Ahmed S. orcidid: 0000-0002-2601-4924 surname: Hussein fullname: Hussein, Ahmed S. email: ashussein@sharjah.ac.ae organization: Department of Electrical and Computer Engineering, University of Sharjah, Sharjah, UAE – sequence: 2 givenname: Anwar H. orcidid: 0000-0002-1873-2088 surname: Jarndal fullname: Jarndal, Anwar H. email: ajarndal@sharjah.ac.ae organization: Department of Electrical and Computer Engineering, University of Sharjah, Sharjah, UAE
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SubjectTerms	Capacitance Computer simulation Electron mobility Gallium nitride GaN high electron mobility transistor (HEMT) HEMTs High electron mobility transistors Mathematical models MODFETs Optimization Parameters parameters extraction Particle swarm optimization particle swarm optimization (PSO) Reliability Semiconductor devices small-signal modeling Solid modeling
Title	Reliable Hybrid Small-Signal Modeling of GaN HEMTs Based on Particle-Swarm-Optimization
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