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Exploring semantically optimized end to end learning solutions for Wireless Communications using Deep Learning

Deep-Learning-based-Wireless-Communications

Reproducible code for the paper: "Semantically Optimized End-to-End Learning for Positional Telemetry in Vehicular Scenarios" accepted at The 19th International Conference on Wireless and Mobile Computing, Networking and Communications 2023

Cite us as:

  • Plain text:

    N. Roy, S. Mostafavi and J. Gross, "Semantically Optimized End-to-End Learning for Positional Telemetry in Vehicular Scenarios," 2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Montreal, QC, Canada, 2023, pp. 425-430, doi: 10.1109/WiMob58348.2023.10187801.
    
  • BibLatex/BibTex:

    @INPROCEEDINGS{10187801,
    author={Roy, Neelabhro and Mostafavi, Samie and Gross, James},
    booktitle={2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)}, 
    title={Semantically Optimized End-to-End Learning for Positional Telemetry in Vehicular Scenarios}, 
    year={2023},
    volume={},
    number={},
    pages={425-430},
    doi={10.1109/WiMob58348.2023.10187801}}
    
    

(https://arxiv.org/abs/2305.03877 and https://ieeexplore.ieee.org/document/10187801)