10 citations · 22 across the 12 of their papers we have counts for
15 papers
Flexible Robust Beamforming for Multibeam Satellite Downlink using Reinforcement Learning
Alea Schröder, Steffen Gracla, Maik Röper +3
Low Earth Orbit (LEO) satellite-to-handheld connections herald a new era in satellite communications. Space-Division Multiple Access (SDMA) precoding is a method that mitigates int…
Scheduling for On-Board Federated Learning with Satellite Clusters
Nasrin Razmi, Bho Matthiesen, Armin Dekorsy +1
Mega-constellations of small satellites have evolved into a source of massive amount of valuable data. To manage this data efficiently, on-board federated learning (FL) enables sat…
RAN Functional Split Options for Integrated Terrestrial and Non-Terrestrial 6G Networks
Mohamed Rihan, Tim Due, MohammadAmin Vakilifard +2
Leveraging non-terrestrial platforms in 6G networks holds immense significance as it opens up opportunities to expand network coverage, enhance connectivity, and support a wide ran…
A Multi-Task Approach to Robust Deep Reinforcement Learning for Resource Allocation
Steffen Gracla, Carsten Bockelmann, Armin Dekorsy
With increasing complexity of modern communication systems, machine learning algorithms have become a focal point of research. However, performance demands have tightened in parall…
On the Importance of Exploration for Real Life Learned Algorithms
Steffen Gracla, Carsten Bockelmann, Armin Dekorsy
The quality of data driven learning algorithms scales significantly with the quality of data available. One of the most straight-forward ways to generate good data is to sample or…
Robust Deep Reinforcement Learning Scheduling via Weight Anchoring
Steffen Gracla, Edgar Beck, Carsten Bockelmann +1
Questions remain on the robustness of data-driven learning methods when crossing the gap from simulation to reality. We utilize weight anchoring, a method known from continual lear…