Master Thesis on Mesh Networking for Drone Swarms (f/m/d)

Dlr; Oberpfaffenhofen; Remote; EUR 11,000 - 17,000; Part time

Job summary

DLR invites a Master Thesis student to explore mesh networking for drone swarms at Oberpfaffenhofen. The project focuses on DECT NR+ PHY/MAC, drone communication topologies, and ML/RL techniques, with evaluation through simulations.

The work combines communications theory and machine learning, offering an opportunity to contribute to next-generation decentralized drone networks within a collaborative research environment.

Qualifications

• Good knowledge of communication systems and signal processing, with emphasis on PHY/MAC protocols.
• Knowledge of ML/RL algorithms.
• Programming skills in C/C++.
• Experience with event-driven network simulations is a plus.
• Ability to work independently and pursue interdisciplinary topics.
• Good knowledge of English language.

Responsibilities

• Familiarize with the DECT-NR+ PHY/MAC standard.
• Study the application to drone communications, considering traffic, topology and channel impairments.
• Evaluate via simulations the protocol operations for mesh networking in drone swarms.
• Explore ML/RL solutions to design semantic networking for drone swarms using DECT NR+.

Skills

C/C++ programming

Machine learning / RL

English proficiency

Event-driven network simulations

Interdisciplinary work

Signal processing basics

Job description

Master Thesis on Mesh Networking for Drone Swarms (f/m/d) Language Profile

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Master Thesis on Mesh Networking for Drone Swarms (f/m/d) Job Description Req ID: 5790 Place of work: Oberpfaffenhofen Starting date: 01.11.2026 Career level: Student research project and final thesis Type of employment: Part time, Full-time Duration of contract: 6 months

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund).

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our12,000employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge?Then this is your place!

The DLR Institute of Communications and Navigation is dedicated to mission-oriented research in selected areas of communications and navigation. Its work ranges from the theoretical foundations to the demonstration of new procedures and systems in a real environment and is embedded in DLR's Space, Aeronautics, Transport, Security and Digitalization programmes.

What to expect

The Advanced Information Processing Group aims at applying state-of-the-art theoretical results into real-world applications within information processing systems. The expertise of the group ranges from quantum error correction to Smart Data Management, exploring cutting-edge communication theories such as semantic communication and Age of Information, pushing the boundaries of data utilization and dissemination.

The thesis will focus on the analysis and evaluation of advanced 5G networking protocols to support efficient and reliable communications in drone swarms, considering also the application of ML/RL solutions. Specifically, the use of DECT NR, world’s first non-cellular radio standard to be formally approved as part of the 5G standards by the ITU, will be investigated. The solution enables decentralized protocols in license-exempt spectrum, and can be a fundamental enabler for advanced drone communications.

Your tasks

• Familiarize with the physical and MAC layer of the DECT-NR+ standard
• Study the application of the solution to drone communications, considering traffic requirements as well as constraints in terms of topology and channel impairments
• Evaluate by means of simulations, the protocol operations and evaluate its suitability for mesh networking in drone swarms for selected applications.
• Consider the use of machine learning/reinforcement learning solutions to design semantic networking protocols for drone swarms that communicate using DECT NR+

Your profile

• Good knowledge of communication systems and signal processing, with particular emphasis on PHY and MAC level protocols.
• Knowledge of ML/RL algorithms
• Programming skills (C/C++) and willingness to learn new tools
• Previous experience with event-driven network simulations is a plus
• Ability to work independently and interest in interdisciplinary topics
• Good knowledge of English language

We offer

We offer
DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 5790) please contact:

Dr. Andrea Munari
Tel.: [phone]