Master's Thesis (wmd) Mesh Networks for 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

Pay: Paid by a fixed pay scale (TVöD)
Language needed: German and English
Subject you study: Communications Engineering, Signal Processing, Computer Science, Machine Learning

Familiarize yourself with the PHY and MAC layer of the DECT-NR+ standard
Investigate the application of the solution for drone communication considering traffic requirements, topology constraints, and channel disturbances
Evaluate the protocol's functionality through simulations and assess its suitability for mesh networks in drone swarms for selected use cases
Examine the use of machine learning and reinforcement learning solutions for developing semantic network protocols for drone swarms communicating via DECT NR+

Sound knowledge in communications systems and signal processing, with particular emphasis on PHY and MAC layer protocols
Knowledge of ML/RL algorithms
Programming skills (C/C++) and willingness to learn new tools
Experience with event-driven network simulations is an advantage
Ability to work independently and interest in interdisciplinary topics
Good English skills

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 further training opportunities are available. Equal opportunities are a particular concern for us; we therefore aim to increase the proportion of women in science and leadership. Applications from severely disabled persons are given preference in case of professional suitability.

Familiarize yourself with the PHY and MAC layer of the DECT-NR+ standard
Investigate the application of the solution for drone communication considering traffic requirements, topology constraints, and channel disturbances
Evaluate the protocol's functionality through simulations and assess its suitability for mesh networks in drone swarms for selected use cases
Examine the use of machine learning and reinforcement learning solutions for developing semantic network protocols for drone swarms communicating via DECT NR+

Sound knowledge in communications systems and signal processing, with particular emphasis on PHY and MAC layer protocols
Knowledge of ML/RL algorithms
Programming skills (C/C++) and willingness to learn new tools
Experience with event-driven network simulations is an advantage
Ability to work independently and interest in interdisciplinary topics
Good English skills

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 further training opportunities are available. Equal opportunities are a particular concern for us; we therefore aim to increase the proportion of women in science and leadership. Applications from severely disabled persons are given preference in case of professional suitability.