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Physics-Based Multi-Bias RF Large-Signal GaN HEMT Modeling and Parameter Extraction Flow
- Source :
- Macquarie University, IEEE Journal of the Electron Devices Society, Vol 5, Iss 5, Pp 310-319 (2017)
- Publication Year :
- 2017
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2017.
-
Abstract
- In this paper, a consistent DC to RF modeling solution for Al gallium nitride (GaN)/GaN high electron mobility transistors is demonstrated that is constructed around a surface-potential-based core. Expressions for drain current and intrinsic terminal charges in the form of surface-potential are used to simultaneously model the DC characteristics and the intrinsic capacitances of a commercial GaN device. Self-heating and trapping effects are incorporated to account for the non-linear nature of the device. We discuss the parameter extraction flow for some of the key model parameters that are instrumental in fitting the DC characteristics, which simultaneously determines the bias-dependent intrinsic capacitances and conductances that significantly eases the RF parameter extraction. Parasitic capacitances, gate finger resistance, and extrinsic bus-inductances are extracted, from a single set of measured non-cold-FET S-parameters, using the model process design kit. The extraction procedure is validated through overlays of broadband (0.5-50 GHz) S-parameters, load-pull and harmonic-balance (10 GHz) simulations against measured data, under multiple bias conditions to successfully demonstrate the model performance at large-signal RF excitations.
- Subjects :
- Materials science
Gallium nitride
02 engineering and technology
High-electron-mobility transistor
01 natural sciences
Capacitance
Signal
law.invention
chemistry.chemical_compound
law
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
Electronic engineering
Electrical and Electronic Engineering
parameter extraction
010302 applied physics
business.industry
GaN HEMT
Load pull
Transistor
load-pull
020206 networking & telecommunications
Electronic, Optical and Magnetic Materials
chemistry
physics-based RF compact model
Logic gate
Optoelectronics
lcsh:Electrical engineering. Electronics. Nuclear engineering
Radio frequency
business
lcsh:TK1-9971
Biotechnology
Subjects
Details
- ISSN :
- 21686734
- Volume :
- 5
- Database :
- OpenAIRE
- Journal :
- IEEE Journal of the Electron Devices Society
- Accession number :
- edsair.doi.dedup.....7fadf3ef257032c94ce4b456420bc348
- Full Text :
- https://doi.org/10.1109/jeds.2017.2724839