activity
20142024
most citedMassive Machine-type Communications in 5G: Physical and MAC-layer solutions

784 citations · 1.2k across the 33 of their papers we have counts for

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Showing 2023Show all

11 papers · 1 filter

cs.NI2023

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…

cs.IT2023★ 57 cited

On-board Federated Learning for Satellite Clusters with Inter-Satellite Links

Nasrin Razmi, Bho Matthiesen, Armin Dekorsy +1

The emergence of mega-constellations of interconnected satellites has a major impact on the integration of cellular wireless and non-terrestrial networks, while simultaneously offe…

eess.SP2023★ 5 cited

Model-free Reinforcement Learning of Semantic Communication by Stochastic Policy Gradient

Edgar Beck, Carsten Bockelmann, Armin Dekorsy

Following the recent success of Machine Learning tools in wireless communications, the idea of semantic communication by Weaver from 1949 has gained attention. It breaks with Shann…

cs.LG2023

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…

cs.LG2023

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…

cs.LG2023

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…

eess.SY2023

Learning Resource Scheduling with High Priority Users using Deep Deterministic Policy Gradients

Steffen Gracla, Edgar Beck, Carsten Bockelmann +1

Advances in mobile communication capabilities open the door for closer integration of pre-hospital and in-hospital care processes. For example, medical specialists can be enabled t…

eess.SP2023

Learning Model-Free Robust Precoding for Cooperative Multibeam Satellite Communications

Steffen Gracla, Alea Schröder, Maik Röper +3

Direct Low Earth Orbit satellite-to-handheld links are expected to be part of a new era in satellite communications. Space-Division Multiple Access precoding is a technique that re…

eess.SP2023

Energy and Bandwidth Efficiency of Event-Based Communication

Christopher Willuweit, Carsten Bockelmann, Armin Dekorsy

Wireless sensor nodes need a drastically reduced technical complexity to fit constraints of future applications. Reducing complexity often results in a degradation of energy and ba…

eess.SP2023

Robust Precoding via Characteristic Functions for VSAT to Multi-Satellite Uplink Transmission

Maik Röper, Bho Matthiesen, Dirk Wübben +2

The uplink from a very small aperture terminal (VSAT) towards multiple satellites is considered, in this paper. VSATs can be equipped with multiple antennas, allowing parallel tran…

cs.IT2023★ 10 cited

A Comparison between RSMA, SDMA, and OMA in Multibeam LEO Satellite Systems

Alea Schröder, Maik Röper, Dirk Wübben +3

Low Earth orbit (LEO) satellite systems enable close to global coverage and are therefore expected to become important pillars of future communication standards. However, a particu…