Automated top-down pruning optimization approach in RF power amplifier designs

Lida Kouhalvandi*, Osman Ceylan, Serdar Ozoguz

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3 Atıf (Scopus)

Özet

This study presents an automated high-accuracy optimization approach for designing high-performance radio frequency high power amplifiers (HPAs). The amplifier is designed by applying a top-down pruning optimization approach that automatically converts the given HPA with lumped elements (LEs) to the HPA with distributed elements (DEs). Firstly, the lumped element HPA is designed based on a bottom-up optimization presented in Kouhalvandi et al. (2019 11th international conference on electrical and electronics engineering (ELECO), pp 510–513, 2019, 10.23919/ELECO47770.2019.8990407), then the LE amplifier is decomposed into basic unit cells that consist of one capacitor (C) and one inductor (L). For each LC unit, a suitable transmission line cell network is selected from predefined models by considering the maximum a posterior (MAP) metric. The component values of the resulting HPA design with DEs are optimized using Bayesian Optimization to achieve the desired design specifications. The overall proposed automated optimization accelerates the design process and outperforms the amplifier’s specifications that is constructed with DEs, automatically. The optimization starts with LE amplifier designs for keeping high linear gain performance and is converted to the HPA with transmission lines for having ready to fabricate circuit design. The proposed approach is validated by designing three HPAs with GaN HEMT from 1.8 to 2.2 GHz operational band frequency with drain efficiency more than 50% and with minimum linear power gain of 14.5 dB in all band frequency.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)525-534
Sayfa sayısı10
DergiAnalog Integrated Circuits and Signal Processing
Hacim106
Basın numarası3
DOI'lar
Yayın durumuYayınlandı - Mar 2021

Bibliyografik not

Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Finansman

This work was 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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