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- Avolio, G., et al.
(författare)
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Millimeter-Wave FET Nonlinear Modelling Based on the Dynamic-Bias Measurement Technique
- 2014
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Ingår i: IEEE Transactions on Microwave Theory and Techniques. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9480 .- 1557-9670. ; 62:11, s. 2526-2537
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Tidskriftsartikel (refereegranskat)abstract
- In the paper, the nonlinear model of a microwave transistor is extracted from large-signal measurements acquired under "dynamic-bias" operation. Specifically, the transistor is driven by low-frequency large signals while a high-frequency tickle is applied on top of them. The low-frequency large signals, along with the dc bias voltages, set the large-signal operating point which represents a dynamic-bias condition for the device under test. Thanks to this technique, one can get at once and separately the nonlinear currents and charges of the transistor as a result of a very few nonlinear measurements. Additionally, the proposed technique allows one to accurately reconstruct the time-domain waveforms at the device-under-test terminals while the frequency of the tickle can be set as high as the bandwidth of today's vector calibrated nonlinear measurement systems (i.e., 67 GHz). The approach, which is general and independent of device technology, is applied on a 0.15-mu m GaAs pHEMT specifically designed for resistive cold-FET mixer applications.
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- Avolio, G., et al.
(författare)
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Nonlinear model for 40-GHz cold-FET operation
- 2014
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Ingår i: International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2014.
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Konferensbidrag (refereegranskat)abstract
- We extract the nonlinear model of a 0.15 μm GaAs pHEMT for cold-FET mixer applications. The model parameters are extracted from experimental data obtained by simultaneously driving the device under test with low-frequency large signals and a tickle tone at the RF operating frequency. The advantage of this approach is twofold. Firstly, as a result of a single measurement one can get separately the nonlinear currents and charge. Secondly, one can perform nonlinear characterization, and subsequently modeling, even if the RF frequency is such that its harmonics cannot be measured by today's nonlinear network vector analyzers.
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- Avolio, G., et al.
(författare)
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Small-Versus Large-Signal Extraction of Charge Models of Microwave FETs
- 2014
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Ingår i: IEEE Microwave and Wireless Components Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-1764 .- 1531-1309. ; 24:6, s. 394-396
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Tidskriftsartikel (refereegranskat)abstract
- In this letter we extract the parameters of the charge equations of a microwave transistor nonlinear model which is available in commercial CAD tools. In particular, the charge model parameters are extracted starting from small- and large-signal measurements. A better accuracy can be achieved when using large-signal measurements since the model parameters are obtained from experimental data which better reproduce the actual operating condition of the device under test. An advanced 0.15 x 300 mu m(2) pHEMT in GaAs technology, aimed at cold-FET mixer design, is considered as case study.
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- Avolio, G., et al.
(författare)
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A novel technique for the extraction of nonlinear model for microwave transistors under dynamic-bias operation
- 2013
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Ingår i: IEEE MTT-S International Microwave Symposium Digest. - 0149-645X. - 9781467361767 ; , s. Art. no. 6697394-
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Konferensbidrag (refereegranskat)abstract
- In this work we describe a novel technique for the extraction of nonlinear model for microwave transistors from nonlinear measurements obtained by simultaneously driving the device under test with low- and high-frequency excitations. Specifically, the large-signal operating point of the device is set by large-signal low-frequency excitations. On top of these a tickle tone at high-frequency is applied. In this way, one can separate the contributions of the IDS current source and the charge sources by a single measurement. The nonlinear model, based on equations available in commercial CAD tools, is extracted for a 0.15 μm GaAs pHEMT. Good agreement is obtained between model predictions and experimental data.
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- Avolio, G., et al.
(författare)
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Identification technique of FET model based on vector nonlinear measurements
- 2011
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Ingår i: Electronics Letters. - : Institution of Engineering and Technology (IET). - 1350-911X .- 0013-5194. ; 47:24, s. 1323-U37
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Tidskriftsartikel (refereegranskat)abstract
- A new modelling approach which exploits only vector nonlinear measurements is described. The parameters of the I-V and Q-V nonlinear constitutive functions are identified by combining low-and high-frequency large-signal measurements with a numerical optimisation routine. Low-frequency dispersion manifesting in the I-V characteristics is also correctly accounted for. As a case study a gallium nitride HEMT on silicon carbide substrate is considered and very good agreement between measurements and simulation is achieved.
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- Avolio, G., et al.
(författare)
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Waveforms-based large-signal identification of transistor models
- 2012
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Ingår i: IEEE MTT-S International Microwave Symposium Digest. - 0149-645X. - 9781467310871
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Konferensbidrag (refereegranskat)abstract
- Measurements of low-and high-frequency vector-calibrated large-signal waveforms are exploited in this work to identify the parameters of a FET nonlinear model. The I DS nonlinear current source and the nonlinear charge sources' parameters are respectively determined from a small set of low-(2 MHz) and high-frequency (8 GHz) load-pull measurements by using a least square numerical optimization. Under low-frequency operation the contribution of the charge sources and any other reactive element can be neglected. In this way the identification of the IDS parameters is more accurate while remarkably speeding up the optimization routine as well. The proposed procedure is quite general and can be applied to different types of active devices. As case study, a 0.25-μm GaAs pHEMT is considered and the extracted model is validated under conditions different than the ones exploited within the identification step. A very good agreement between model predictions and experimental data is achieved.
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