## Abstract A radial‐basis function neural network (RBFNN) approach is proposed for predicting the nonlinear behaviors of gallium nitride (GaN) Doherty amplifier. Sampled input and output data from a designed GaN Doherty amplifier were used to train and test the proposed RBFNN model. Comparison of
Behavioral modeling of power amplifiers for wireless applications
✍ Scribed by Konstantinos S. Vryssas; Apostolos Samelis
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 707 KB
- Volume
- 17
- Category
- Article
- ISSN
- 1096-4290
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✦ Synopsis
In this paper, an improved empirical behavioral model for radio-frequency power amplifiers (RF-PAs) is presented. The model was implemented in a commercial nonlinear microwave simulator. It belongs to the category of bandpass PA models, which exhibits memory effects due to the low frequency dependence of bias and temperature. Additionally, it facilitates accurate and efficient system level simulations of RF-PA large-signal behaviors such as self-bias, AM-AM, AM-PM, gain expansion effects, and intermodulation distortion (IMD) sweet-spots. The model was validated using measurement data obtained from a commercial CDMA PA at 1.88 GHz. V
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