Automated Two-Step Power Amplifier Design with Pre-constructed Artificial Neural Network

Lida Kouhalvandi, Marco Pirola, Serdar Ozoguz

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

7 Atıf (Scopus)

Özet

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.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2020 43rd International Conference on Telecommunications and Signal Processing, TSP 2020
EditörlerNorbert Herencsar
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar617-620
Sayfa sayısı4
ISBN (Elektronik)9781728163765
DOI'lar
Yayın durumuYayınlandı - Tem 2020
Etkinlik43rd International Conference on Telecommunications and Signal Processing, TSP 2020 - Milan, Italy
Süre: 7 Tem 20209 Tem 2020

Yayın serisi

Adı2020 43rd International Conference on Telecommunications and Signal Processing, TSP 2020

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???event.eventtypes.event.conference???43rd International Conference on Telecommunications and Signal Processing, TSP 2020
Ülke/BölgeItaly
ŞehirMilan
Periyot7/07/209/07/20

Bibliyografik not

Publisher Copyright:
© 2020 IEEE.

Finansman

This work is supported by Istanbul Technical University the Scientific Research Projects Unit, Under Grant No. MDK-2019-41968.

FinansörlerFinansör numarası
Istanbul Technical University the Scientific Research Projects UnitMDK-2019-41968

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