Master's Thesis (f/m/d) Semantically-Oriented PHY Techniques for Communication in Drone Swarms

Deutsches Zentrum für Luft- und Raumfahrt e.V.

ThesisGerman needed: not said

Still open on 1 Nov

You apply on the company's own website.

Key facts

Investigate how relevant, task-specific information (i.e., features) can be extracted from radio signals instead of transmitting raw data, with the aim of reducing data volume while retaining the semantic information needed for cooperative localisation and tracking
Evaluate the approach through software simulations, analysing the impact of channel effects (e.g., multipath propagation, Doppler effect) on the accuracy of the extracted information required for reliable operation of higher layers
Gain practical experience by testing the developed methods on real hardware platforms (e.g., SDR, UWB modules, flying drones), including implementation of the signal processing chain for real-time operation in airborne environments
Collaborate with the team working on higher protocol layers to define the optimal trade-off between raw and processed data transmission to maximise swarm efficiency

Solid knowledge of communication systems, signal processing, and wireless networks
Interest in AI-based signal processing (feature extraction, classification) and semantic communication
Experience with SDR platforms, radio hardware, and embedded systems (software testing on hardware) is an advantage
Programming skills in C/C++, MATLAB, and Python
Ability to work independently and interest in interdisciplinary topics (PHY protocols, AI, and hardware)

DLR stands for diversity, appreciation, and equality for all people. We promote independent work and the individual development of our employees in their personal and professional environment. For this purpose, our numerous training and further education opportunities are available to you. Equal opportunities are a particular concern for us; we therefore aim to increase the proportion of women in science and management. Applications from severely disabled persons are given preference in case of professional suitability.

Investigate how relevant, task-specific information (i.e., features) can be extracted from radio signals instead of transmitting raw data, with the aim of reducing data volume while retaining the semantic information needed for cooperative localisation and tracking
Evaluate the approach through software simulations, analysing the impact of channel effects (e.g., multipath propagation, Doppler effect) on the accuracy of the extracted information required for reliable operation of higher layers
Gain practical experience by testing the developed methods on real hardware platforms (e.g., SDR, UWB modules, flying drones), including implementation of the signal processing chain for real-time operation in airborne environments
Collaborate with the team working on higher protocol layers to define the optimal trade-off between raw and processed data transmission to maximise swarm efficiency

Solid knowledge of communication systems, signal processing, and wireless networks
Interest in AI-based signal processing (feature extraction, classification) and semantic communication
Experience with SDR platforms, radio hardware, and embedded systems (software testing on hardware) is an advantage
Programming skills in C/C++, MATLAB, and Python
Ability to work independently and interest in interdisciplinary topics (PHY protocols, AI, and hardware)

DLR stands for diversity, appreciation, and equality for all people. We promote independent work and the individual development of our employees in their personal and professional environment. For this purpose, our numerous training and further education opportunities are available to you. Equal opportunities are a particular concern for us; we therefore aim to increase the proportion of women in science and management. Applications from severely disabled persons are given preference in case of professional suitability.