Model-Driven End-to-End Learning for Integrated Sensing and Communication
Author:
Affiliation:
1. Chalmers University of Technology,Department of Electrical Engineering,Sweden
2. Univ Rennes, INSA Rennes, CNRS, IETR-UMR 6164,Rennes,France
Funder
European Commission
Swedish Research Council
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10278505/10278554/10278889.pdf?arnumber=10278889
Reference34 articles.
1. Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks: A Deep Learning Approach
2. Integrated Sensing and Communication-Enabled Predictive Beamforming With Deep Learning in Vehicular Networks
3. Similarity-Based Prediction for Channel Mapping and User Positioning
4. End-to-End Learning for Integrated Sensing and Communication
5. Learning-Based Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks
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1. Semi-Supervised End-to-End Learning for Integrated Sensing and Communications;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05
2. Loss Design for Single-carrier Joint Communication and Neural Network-based Sensing;2024 27th International Workshop on Smart Antennas (WSA);2024-03-17
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