7 papers
Model-Free Robust Beamforming in Satellite Downlink using Reinforcement Learning
Alea Schröder, Steffen Gracla, Carsten Bockelmann +2
Satellite-based communications are expected to be a substantial future market in 6G networks. As satellite constellations grow denser and transmission resources remain limited, fre…
Compressed Learning for Nanosurface Deficiency Recognition Using Angle-resolved Scatterometry Data
Mehdi Abdollahpour, Carsten Bockelmann, Tajim Md Hasibur Rahman +2
Nanoscale manufacturing requires high-precision surface inspection to guarantee the quality of the produced nanostructures. For production environments, angle-resolved scatterometr…
CQI-Based Interference Prediction for Link Adaptation in Industrial Sub-networks
Pramesh Gautam, Ravi Sharan Bhagavathula, Paolo Baracca +3
We propose a novel interference prediction scheme to improve link adaptation (LA) in densely deployed industrial sub-networks (SNs) with high-reliability and low-latency communicat…
Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks
Pramesh Gautam, Sushmita Sapkota, Carsten Bockelmann +2
Interference prediction that accounts for extreme and rare events remains a key challenge for ultra-densely deployed sub-networks (SNs) requiring hyper-reliable low-latency communi…
Semantic Communication for Cooperative Multi-Tasking over Rate-Limited Wireless Channels with Implicit Optimal Prior
Ahmad Halimi Razlighi, Carsten Bockelmann, Armin Dekorsy
In this work, we expand the cooperative multi-task semantic communication framework (CMT-SemCom) introduced in [1], which divides the semantic encoder on the transmitter side into…
Dynamic Interference Prediction for In-X 6G Sub-networks
Pramesh Gautam, Ravi Sharan Bhagavathula, Paolo Baracca +3
The sixth generation (6G) industrial Sub-networks (SNs) face several challenges in meeting extreme latency and reliability requirements in the order of 0.1-1 ms and 99.999 -to-99.9…