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Journal of Computational Electronics
Erschienen in: Journal of Computational Electronics 4/2014

01.12.2014

Linearization design method in class-F power amplifier using artificial neural network

verfasst von: Mohsen Hayati, Farzin Shama, Sobhan Roshani, Abdolali Abdipour

Erschienen in: Journal of Computational Electronics | Ausgabe 4/2014

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Abstract

This paper represents the design of a class-F power amplifier (PA), its artificial neural network (ANN) model and a PA linearization method. The designed PA operates at 1.8 GHz with gain of 12 dB and 1dB output compression point (P1dB) of 36 dBm. The proposed ANN model is used to predict the output power of designed class-F PA as a function of input and DC power. This model utilizes the designed class-F PA as a block, which could be used in a desired linearization circuit. In addition, the power added efficiency (PAE) and the other specifications of a PA, related to power can be predicted using the proposed model. A simple feedforward technique is used to improve the linearity of designed PA. For verification, this linearization method is compared with presented neural network model simulations. The results show the improvement of P1dB from 36 to 41 dBm, which is predicted using the proposed model. Also, the PAE of the final linearized circuit PA is predicted.
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Metadaten
Titel
Linearization design method in class-F power amplifier using artificial neural network
verfasst von
Mohsen Hayati
Farzin Shama
Sobhan Roshani
Abdolali Abdipour
Publikationsdatum
01.12.2014
Verlag
Springer US
Erschienen in
Journal of Computational Electronics / Ausgabe 4/2014
Print ISSN: 1569-8025
Elektronische ISSN: 1572-8137
DOI
https://doi.org/10.1007/s10825-014-0612-x

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