12 papers
Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks
Ahmad Halimi Razlighi, Mohammad Siddiqur Rahman, Maximilian H. V. Tillmann +2
Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent networks. In our prior work […
Optimized Sampling of Angle-Resolved Scatterometry Data Using End-to-End Compressed Learning Model for Nanograss Deficiency Detection
Mehdi Abdollahpour, Carsten Bockelmann, Armin Dekorsy
Reliable inspection of nanosurfaces is essential to ensure the quality of nanostructure manufacturing. Angle-resolved scatterometry provides a non-invasive inspection method that c…
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…
Semantic Communication for Task Execution and Data Reconstruction in Multi-View Scenarios
Maximilian H. V. Tillmann, Avinash Kankari, Carsten Bockelmann +1
Semantic communication has gained significant attention with the advances in machine learning. Most semantic communication works focus on either task execution or data reconstructi…
Semantic Joint Source Channel Coding for Distributed Subsurface Imaging in Multi-Agent Systems
Maximilian H. V. Tillmann, Ban-Sok Shin, Dmitriy Shutin +1
Multi-agent systems (MASs) are a promising solution for autonomous exploration tasks in hazardous or remote environments. In such settings, communication among agents is essential…
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…
Integrating Semantic Communication and Human Decision-Making into an End-to-End Sensing-Decision Framework
Edgar Beck, Hsuan-Yu Lin, Patrick Rückert +5
As early as 1949, Weaver defined communication in a very broad sense to include all procedures by which one mind or technical system can influence another, thus establishing the id…
Cooperative and Collaborative Multi-Task Semantic Communication for Distributed Sources
Ahmad Halimi Razlighi, Maximilian H. V. Tillmann, Edgar Beck +2
In this paper, we explore a multi-task semantic communication (SemCom) system for distributed sources, extending the existing focus on collaborative single-task execution. We build…