Loadpull Behavioral Modeling for Power Amplifiers Under Modulated Operating Conditions

We offer a novel modeling technique for characterizing the behavior of power amplifiers under modulated operating conditions. Our model considers the impact of memory effects and impedance variations separately and in sequence of one another, which enables us to simplify the measurement procedure as well as the data analysis methodology while maintaining accuracy and repeatability. We reduce the complexity of this behavioral modeling problem via various assumptions which we validate against measured data. Our model simplifications allow us to describe power amplifier loadpull behavior with high accuracy (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&lt;-27 \text{dB}$</tex> NMSE) using low-order Volterra polynomials, demonstrating that simple and efficient analytical techniques suffice to approximate this complex problem.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/arftg65332.2025.11168139
Primary Topic
Methodologies in Health Research and Practice
Type
article
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article

Loadpull Behavioral Modeling for Power Amplifiers Under Modulated Operating Conditions

Methodologies in Health Research and Practice
article

Loadpull Behavioral Modeling for Power Amplifiers Under Modulated Operating Conditions

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Abstract

We offer a novel modeling technique for characterizing the behavior of power amplifiers under modulated operating conditions. Our model considers the impact of memory effects and impedance variations separately and in sequence of one another, which enables us to simplify the measurement procedure as well as the data analysis methodology while maintaining accuracy and repeatability. We reduce the complexity of this behavioral modeling problem via various assumptions which we validate against measured data. Our model simplifications allow us to describe power amplifier loadpull behavior with high accuracy (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&lt;-27 \text{dB}$</tex> NMSE) using low-order Volterra polynomials, demonstrating that simple and efficient analytical techniques suffice to approximate this complex problem.

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Methodologies in Health Research and Practice
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