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

Lida Kouhalvandi*, Osman Ceylan, Serdar Ozoguz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)525-534
Number of pages10
JournalAnalog Integrated Circuits and Signal Processing
Volume106
Issue number3
DOIs
Publication statusPublished - Mar 2021

Bibliographical note

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

Funding

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

FundersFunder number
Istanbul Technical University the Scientific Research Projects UnitMDK-2019-41968

    Keywords

    • Automated
    • Bayesian optimization
    • Bottom-up optimization
    • Distributed element (DE)
    • GaN HEMT
    • High power amplifier (HPA)
    • Lumped element (LE)
    • Matching network (MN)
    • Top-down pruning optimization

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