Nonlinear Electrothermal GaN HEMT Model Applied to High-Efficiency Power Amplifier Design

King, Justin; Brazil, T.J.

doi:10.1109/tmtt.2012.2229712

Cited by 92 publications

(49 citation statements)

References 24 publications

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“…The accuracy of the model can be improved by adjusting the equivalent circuit topology, and as the Bayesian approach is effectively independent of the underlying model, this can be achieved with relative ease. 16 The kink-effect, which originates mainly from the high values of gm 32,33 inherent to GaN HEMT devices, can be observed from the plot of S 22 in Figure 12. As can be seen from the test example in Figure 12, the proposed model provides a good prediction of the kink-effect.…”

Section: Bayesian Inference-based Equivalent Circuit Modelmentioning

confidence: 99%

“…This is mainly due to the limitations of the topology of the standard HEMT equivalent circuit model, for example, trapping, and higher order distributed/nonquasi‐static effects are not taken into account. The accuracy of the model can be improved by adjusting the equivalent circuit topology, and as the Bayesian approach is effectively independent of the underlying model, this can be achieved with relative ease …”

Section: Bayesian Inference‐based Equivalent Circuit Modelmentioning

confidence: 99%

“…Various different modeling approaches have been developed, for example, references [11][12][13][14][15][16][17] , most of which can be clearly categorized as either behavioral models, or equivalent circuit models. Considering first behavioral modeling methods, several key frequency-domain approaches have been reported in the literature, which are capable of reasonably accurate predictions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Bayesian inference-based small-signal modeling technique for GaN HEMTs

Cai

King

et al. 2018

Int J RF Microw Comput Aided Eng

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A new modeling methodology for gallium nitride (GaN) high‐electron‐mobility transistors (HEMTs) based on Bayesian inference theory, a core method of machine learning, is presented in this article. Gaussian distribution kernel functions are utilized for the Bayesian‐based modeling technique. A new small‐signal model of a GaN HEMT device is proposed based on combining a machine learning technique with a conventional equivalent circuit model topology. This new modeling approach takes advantage of machine learning methods while retaining the physical interpretation inherent in the equivalent circuit topology. The new small‐signal model is tested and validated in this article, and excellent agreement is obtained between the extracted model and the experimental data in the form of dc I–V curves and S‐parameters. This verification is carried out on an 8 × 125 μm GaN HEMT with a 0.25 μm gate feature size, over a wide range of operating conditions. The dc I–V curves from an artificial neural network (ANN) model are also provided and compared with the proposed new model, with the latter displaying a more accurate prediction benefiting, in particular, from the absence of overfitting that may be observed in the ANN‐derived I–V curves.

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Section: Bayesian Inference-based Equivalent Circuit Modelmentioning

confidence: 99%

Section: Bayesian Inference‐based Equivalent Circuit Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bayesian inference-based small-signal modeling technique for GaN HEMTs

Cai

King

et al. 2018

Int J RF Microw Comput Aided Eng

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“…For these reasons, the GaN technology is considered to be the technology of choice for future designs of microwave power amplifiers (PAs). 3,4 However, GaN HEMTs have demonstrated also good noise performance: its minimum noise figure is quite comparable with the GaAs field-effect transistor (FET), and its high-power handling capabilities eliminate the need of complex protection circuitry. Therefore, the GaN HEMT is an attractive candidate also for designing microwave low-noise amplifiers (LNAs), 5 which accordingly requires reliable noise model of the GaN-based transistor.…”

Section: Introductionmentioning

confidence: 99%

Reliable noise modeling of GaN HEMTs for designing low‐noise amplifiers

Jarndal

Hussein

Crupi

et al. 2019

Int J Numerical Modelling

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A reliable modeling procedure is developed for extracting an equivalent circuit able to reproduce the small-signal and noise performance of the gallium nitride (GaN) high-electron mobility transistor (HEMT) technology. The main advantages of this model are its simplicity and straightforward extraction based on only pinch-off scattering (S-) parameter measurements. The validity of the achieved model is verified by the good agreement between high-frequency experiments and simulations for three devices with different sizes. The model reliability is further confirmed by the observed good scaling of the extracted parameters. The same model is demonstrated by designing and simulating a broadband low-noise amplifier (LNA) for 5G applications.

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“…Nowadays, extensive attention is being paid to the HEMT based on GaN, primarily because of the outstanding physical properties of this wide‐band‐gap semiconductor for microwave high‐power applications . Although research studies have been mainly addressed to analyze the GaN HEMT in terms of power performance, a growing attention is being given also to its noise performance.…”

Section: Introductionmentioning

confidence: 99%

GaN HEMT noise modeling based on 50‐Ω noise factor

Crupi

Caddemi

Raffo

et al. 2015

Micro & Optical Tech Letters

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The extraction of a high-frequency ivalent circuit model plays a fundamental role for the development of any emerging transistor technology. Indeed, an equivalent circuit can provide a valuable support for microwave engineers to ensure a fast and reliable optimization of both device fabrication and circuit design. As far as gallium nitride (GaN) HEMTs are concerned, research efforts have been mostly focused on determining equivalent circuits able to reproduce their large-signal behavior. Nevertheless, an increasing amount of interest is also being devoted to noise equivalent circuits, due to the interesting GaN technology noise performance. Within this context, the purpose of the present paper is to extract and fully validate an accurate noise model for GaN HEMTs based on a simple, fast, and reliable extraction procedure. The noise model is obtained by assigning an equivalent noise temperature to each resistor of the small-signal equivalent circuit. The accuracy of the extracted noise model is confirmed by the good agreement between measured and simulated high-frequency noise parameters

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Nonlinear Electrothermal GaN HEMT Model Applied to High-Efficiency Power Amplifier Design

Cited by 92 publications

References 24 publications

Bayesian inference-based small-signal modeling technique for GaN HEMTs

Bayesian inference-based small-signal modeling technique for GaN HEMTs

Reliable noise modeling of GaN HEMTs for designing low‐noise amplifiers

GaN HEMT noise modeling based on 50‐Ω noise factor

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