Master thesis: Modeling and Intelligent Control of a Dual-Input RF Power Amplifier System – 07/26

Overview

The Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik (FBH) is an application-oriented research institute in high-frequency electronics, photonics and quantum physics. It researches and realizes electronic and optical components, modules and systems based on compound semiconductors. These devices enable advances in fields such as communication, energy, health and mobility.

The focus in the RF Power Lab is on applications with output powers in the range of 5...200 W in the microwave range up to 40 GHz. We develop concepts to increase efficiency in broadband modulated power amplifier systems for modern telecommunication and signals with high peak-to-average power ratios. We investigate dual-input amplifier systems based on load and supply-voltage modulation and their use in AI-controlled intelligent self-tunable systems. Integrated reconfigurable components and circuits, advanced transceivers for radar and telecom, and novel autonomous RF measurement systems for improved RF power transistor characterization are also in scope, including optimization using machine learning.

Reference number 07/26

Your tasks (with focus depending on background)

• Evaluation of a novel behavioral model for a supply voltage modulated dual input dual output (DIDO) system over large temperature variation
• Acquire experimental data for the ET PA at different temperatures T1, T2, …
• Identify model parameters for a recently developed DIDO model for each temperature
• Use machine learning (ML) to create a model for the parameter dependence
• Verify the model against experimental data

• Control and optimization of PA performance for temperature variations
• Develop an ML model for control of the DIDO
• Train the ML model based on the behavioral model in task 1
• Verify the ML model based on experimental data

Your profile

• Ongoing master studies in Computer Science, Electrical Engineering, Communications and Signal Processing, or Physics with Applied Mathematics
• Knowledge of machine learning, signal processing, microwave engineering, nonlinear and behavioral modeling, AI-based modeling
• Interest in applied mathematics, signal processing
• Experience in Matlab and Python (preferably)
• Starting date: ASAP

Our offer

• An open and appreciative international team, always available with help and advice
• A modern workplace in Berlin Adlershof with good public transport connections
• Exciting insights into practical applications and the opportunity to gain valuable experience

Does it sound interesting? Then we look forward to receiving your online application. To apply, please click on "Apply online" and submit your complete application documents by April 13, 2026 .

If you have questions, please contact Dr. Olof Bengtsson, Tel.: , E-Mail:

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