A large-signal model of self-aligned gate GaAs FET's for high-efficiency power-amplifier design

Hirose, Masao; Kitaura, Y.; Uchitomi, Naotaka

doi:10.1109/22.808984

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…The drain conductance frequency dispersion is explained by the electron trapping effect of deep levels in the substrate corresponding to the input signals. The value of resistance R cf is given by the formula []

R_{cf} = \frac{2 \cdot R_{cf 0}}{tanh [B_{fr} \cdot (V_{GS 0} - U_{rc})] + 1}

where R cf0 , U rc , and B rf are fitting parameters.…”

Section: The Model Formmentioning

confidence: 99%

Modeling of MESFET in SPICE including self-heating

Bisewski

Zarębski

2014

Int. J. Numer. Model.

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The paper deals with the problem of modeling and analysis in Simulation Program with Integrated Circuit Emphasis of thermal effects influence on properties of metal–semiconductor field‐effect transistor made of different semiconductor materials, that is, gallium arsenide and silicon carbide. An electrothermal model of the investigated transistors was formulated and experimentally verified. The proper procedure of parameter estimation for the elaborated model was carried out. The evaluation of accuracy and examination of usefulness of the elaborated model have been performed by comparison of measured and calculated devices characteristics. Copyright © 2014 John Wiley & Sons, Ltd.

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R_{cf} = \frac{2 \cdot R_{cf 0}}{tanh [B_{fr} \cdot (V_{GS 0} - U_{rc})] + 1}

where R cf0 , U rc , and B rf are fitting parameters.…”

Section: The Model Formmentioning

confidence: 99%

Modeling of MESFET in SPICE including self-heating

Bisewski

Zarębski

2014

Int. J. Numer. Model.

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Neural networks for microwave modeling: Model development issues and nonlinear modeling techniques

Devabhaktuni

Yagoub

Fang

et al. 2000

Int. J. RF and Microwave Comp. Aid. Eng.

113

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Artificial neural networks ANN recently gained attention as a fast and flexible vehicle to microwave modeling and design. Fast neural models trained from measuredr r r r rsimulated microwave data can be used during microwave design to provide instant answers to the task they have learned. We review two important aspects of neural-network-based microwave modeling, namely, model development issues and nonlinear modeling. A systematic description of key issues in neural modeling approach such as data generation, range and distribution of samples in model input parameter space, data scaling, etc., is presented. Techniques that pave the way for automation of neural model development could be of immense interest to microwave engineers, whose knowledge about ANN is limited. As such, recent techniques that could lead to automatic neural model development, e.g., adaptive controller and adaptive sampling, are discussed. Neural modeling of nonlinear devicer r r r rcircuit characteristics has emerged as an important research area. An overview of nonlinear techniques including smallr r r r rlarge signal neural modeling of ( ) transistors and dynamic recurrent neural network RNN modeling of circuits is presented. Practical microwave examples are used to illustrate the reviewed techniques.

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An Approach to Harmonic Load– and Source–Pull Measurements for High-Efficiency PA Design

Colantonio

Giannini

Limiti

et al. 2004

IEEE Trans. Microwave Theory Techn.

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An antipodal Fermi-linear tapered slot antenna (AFLTSA) is presented for Ka-band applications. A substrate integrated waveguide is used to excite the tapered slot. The proposed design has a measured 26-40 GHz wide impedance bandwidth with a return loss below 15 dB. It maintains a flat gain of 16 dB over an entire frequency band. The knife edges are corrugation profile of AFLTSA exhibits side lobe level of 214 dB in H plane and 219 dB in E plane. It has a symmetric radiation pattern as well as a cross polarization level of 222 dB.

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A large-signal model of self-aligned gate GaAs FET's for high-efficiency power-amplifier design

Cited by 3 publications

References 14 publications

Modeling of MESFET in SPICE including self-heating

Modeling of MESFET in SPICE including self-heating

Neural networks for microwave modeling: Model development issues and nonlinear modeling techniques

An Approach to Harmonic Load– and Source–Pull Measurements for High-Efficiency PA Design

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