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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Veröffentlicht in:IEEE transactions on computer-aided design of integrated circuits and systems Jg. 37; H. 9; S. 1816 - 1824
Hauptverfasser: Hussein, Ahmed S., Jarndal, Anwar H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.09.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
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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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0278-0070
1937-4151
DOI:10.1109/TCAD.2017.2782779