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20212026
most citedSemantic Information Recovery in Wireless Networks

34 citations · 51 across the 11 of their papers we have counts for

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6 papers · 1 filter

eess.SP2026

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 […

eess.SP2026

Semantic-Aware Task Clustering for Federated Cooperative Multi-Task Semantic Communication

Ahmad Halimi Razlighi, Pallavi Dhingra, Edgar Beck +2

Task-oriented semantic communication (SemCom) prioritizes task execution over accurate symbol reconstruction and is well-suited to emerging intelligent applications. Cooperative mu…

eess.SP2024

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…

eess.SP2024

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…

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…

eess.SP2021★ 12 cited

CMDNet: Learning a Probabilistic Relaxation of Discrete Variables for Soft Detection with Low Complexity

Edgar Beck, Carsten Bockelmann, Armin Dekorsy

Following the great success of Machine Learning (ML), especially Deep Neural Networks (DNNs), in many research domains in 2010s, several ML-based approaches were proposed for detec…