DocumentCode
2524230
Title
GaN power amplifier design based on artificial neural network modelling
Author
Xiao, D. ; Schreurs, D. ; De Raedt, W. ; Derluyn, J. ; Balachander, K. ; Viaene, J. ; Germain, M. ; Nauwelaers, B. ; Borghs, G.
Author_Institution
IMEC, Leuven
fYear
2007
fDate
8-10 Oct. 2007
Firstpage
40
Lastpage
43
Abstract
GaN field effect transistors (FETs) have a strong potential for high-power applications. However the RF performance of these devices often experiences limitation due to trapping effects and self-heating. These complicate the development of accurate large-signal models for GaN FETs. To simplify this process, a state-space modelling technique using an artificial neural network (ANN) is used in this work to model the large signal behaviour of the GaN device. In this way, the model is constructed directly from large-signal measurement data collected while the device is in an operating mode close to its application, i.e., class AB power amplifier (PA). To demonstrate the approach, a hybrid power amplifier based on GaN FETs was designed and fabricated. The good agreement between measurements and simulation results verifies the proposed approach. It is the first time that this modelling approach is used in circuit design.
Keywords
field effect transistor circuits; neural nets; power amplifiers; GaN; artificial neural network modelling; field effect transistors; hybrid power amplifier; power amplifier design; state-space modelling technique; Artificial neural networks; Circuit simulation; Circuit synthesis; FETs; Gallium nitride; Power amplifiers; Power measurement; Radio frequency; Radiofrequency amplifiers; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Microwave Integrated Circuit Conference, 2007. EuMIC 2007. European
Conference_Location
Munich
Print_ISBN
978-2-87487-002-6
Type
conf
DOI
10.1109/EMICC.2007.4412642
Filename
4412642
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