An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs

Saif Ur Rehman; Hafiz Fuad Usman; Umer Farooq Ahmed; M. Asif; Soo Young Shin

doi:10.1109/ICTC46691.2019.8939850

An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs

Saif Ur Rehman, Hafiz Fuad Usman, Umer Farooq Ahmed, M. Asif, Soo Young Shin

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

This article focuses on the improved extraction method implemented on 0.5\mu m \times (2\times 50 \mum) AlGaN/GaN High Electron Mobility Transistors (HEMTs) particularly for the high order frequency, power and voltage routine life applications. On the basis of S-parameter extraction at different biasing conditions, small signal modeling has been carried out to extract intrinsic parameters with improved accuracy up to 50 GHz. Particle-swarm-optimization (PSO) technique has been implemented and validated through measured results. It is observed that simulated and measured results are in good agreement at a wide range of frequencies. Furthermore, different performance parameters, such as maximum available and stable gain, and insertion loss are also evaluated.

Original language	English
Title of host publication	ICTC 2019 - 10th International Conference on ICT Convergence
Subtitle of host publication	ICT Convergence Leading the Autonomous Future
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1104-1109
Number of pages	6
ISBN (Electronic)	9781728108926
DOIs	https://doi.org/10.1109/ICTC46691.2019.8939850
Publication status	Published - Oct 2019
Externally published	Yes
Event	10th International Conference on Information and Communication Technology Convergence, ICTC 2019 - Jeju Island, Korea, Republic of Duration: 16 Oct 2019 → 18 Oct 2019

Publication series

Name	ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future

Conference

Conference	10th International Conference on Information and Communication Technology Convergence, ICTC 2019
Country/Territory	Korea, Republic of
City	Jeju Island
Period	16/10/19 → 18/10/19

Keywords

GaN
High electron mobility transistors
Parameters extraction
Particle Swarm Optimization
Small signal modeling

Access to Document

10.1109/ICTC46691.2019.8939850

Cite this

Rehman, S. U., Usman, H. F., Ahmed, U. F., Asif, M., & Shin, S. Y. (2019). An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs. In ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future (pp. 1104-1109). Article 8939850 (ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICTC46691.2019.8939850

Rehman, Saif Ur ; Usman, Hafiz Fuad ; Ahmed, Umer Farooq et al. / An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs. ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1104-1109 (ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future).

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title = "An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs",

abstract = "This article focuses on the improved extraction method implemented on 0.5\mu m \times (2\times 50 \mum) AlGaN/GaN High Electron Mobility Transistors (HEMTs) particularly for the high order frequency, power and voltage routine life applications. On the basis of S-parameter extraction at different biasing conditions, small signal modeling has been carried out to extract intrinsic parameters with improved accuracy up to 50 GHz. Particle-swarm-optimization (PSO) technique has been implemented and validated through measured results. It is observed that simulated and measured results are in good agreement at a wide range of frequencies. Furthermore, different performance parameters, such as maximum available and stable gain, and insertion loss are also evaluated.",

keywords = "GaN, High electron mobility transistors, Parameters extraction, Particle Swarm Optimization, Small signal modeling",

author = "Rehman, {Saif Ur} and Usman, {Hafiz Fuad} and Ahmed, {Umer Farooq} and M. Asif and Shin, {Soo Young}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 10th International Conference on Information and Communication Technology Convergence, ICTC 2019 ; Conference date: 16-10-2019 Through 18-10-2019",

year = "2019",

month = oct,

doi = "10.1109/ICTC46691.2019.8939850",

language = "English",

series = "ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Rehman, SU, Usman, HF, Ahmed, UF, Asif, M & Shin, SY 2019, An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs. in ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future., 8939850, ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future, Institute of Electrical and Electronics Engineers Inc., pp. 1104-1109, 10th International Conference on Information and Communication Technology Convergence, ICTC 2019, Jeju Island, Korea, Republic of, 16/10/19. https://doi.org/10.1109/ICTC46691.2019.8939850

An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs. / Rehman, Saif Ur; Usman, Hafiz Fuad; Ahmed, Umer Farooq et al.
ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1104-1109 8939850 (ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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AU - Asif, M.

AU - Shin, Soo Young

PY - 2019/10

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N2 - This article focuses on the improved extraction method implemented on 0.5\mu m \times (2\times 50 \mum) AlGaN/GaN High Electron Mobility Transistors (HEMTs) particularly for the high order frequency, power and voltage routine life applications. On the basis of S-parameter extraction at different biasing conditions, small signal modeling has been carried out to extract intrinsic parameters with improved accuracy up to 50 GHz. Particle-swarm-optimization (PSO) technique has been implemented and validated through measured results. It is observed that simulated and measured results are in good agreement at a wide range of frequencies. Furthermore, different performance parameters, such as maximum available and stable gain, and insertion loss are also evaluated.

AB - This article focuses on the improved extraction method implemented on 0.5\mu m \times (2\times 50 \mum) AlGaN/GaN High Electron Mobility Transistors (HEMTs) particularly for the high order frequency, power and voltage routine life applications. On the basis of S-parameter extraction at different biasing conditions, small signal modeling has been carried out to extract intrinsic parameters with improved accuracy up to 50 GHz. Particle-swarm-optimization (PSO) technique has been implemented and validated through measured results. It is observed that simulated and measured results are in good agreement at a wide range of frequencies. Furthermore, different performance parameters, such as maximum available and stable gain, and insertion loss are also evaluated.

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Rehman SU, Usman HF, Ahmed UF, Asif M, Shin SY. An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs. In ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1104-1109. 8939850. (ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future). doi: 10.1109/ICTC46691.2019.8939850

An Improved Technique to Assess AC Performance of a Submicron GaN HEMTs

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Keywords

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