Abstract
Power amplifier (PA) designs at high frequency are not straightforward and they depend on designers' experience by dealing with a high number of parameters to be set. To address PA design problems, we propose an automated bottomup method based on an artificial neural network (ANN) to be employed in the optimization-oriented strategy. The proposed methodology starts with a PA based on lumped elements (LEs), then ANN is trained for characterizing the lumped element PA and finally a PA with distributed components, the natural environment at high frequency, is designed by using a bottomup method and the constructed ANN. In this way, the resulting distributed element PA inherits the advantages of the lumped element design, i.e., offering higher and flatter gain performance. To validate our method, we design 10 W PAs in band frequency of 1 GHz to 2 GHz (L band). The automated design of PA with transmission lines (TLs) results in gain between 10-13dB and power added efficiency larger than 50%. Our results demonstrate the robustness of the presented approach adopting ANN in designing PAs, automatically.
Original language | English |
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Title of host publication | 2020 43rd International Conference on Telecommunications and Signal Processing, TSP 2020 |
Editors | Norbert Herencsar |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 617-620 |
Number of pages | 4 |
ISBN (Electronic) | 9781728163765 |
DOIs | |
Publication status | Published - Jul 2020 |
Event | 43rd International Conference on Telecommunications and Signal Processing, TSP 2020 - Milan, Italy Duration: 7 Jul 2020 → 9 Jul 2020 |
Publication series
Name | 2020 43rd International Conference on Telecommunications and Signal Processing, TSP 2020 |
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Conference
Conference | 43rd International Conference on Telecommunications and Signal Processing, TSP 2020 |
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Country/Territory | Italy |
City | Milan |
Period | 7/07/20 → 9/07/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Funding
This work is supported by Istanbul Technical University the Scientific Research Projects Unit, Under Grant No. MDK-2019-41968.
Funders | Funder number |
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Istanbul Technical University the Scientific Research Projects Unit | MDK-2019-41968 |
Keywords
- Artificial neural network
- automated design
- matching network
- power amplifier