Skip to content

pytorch implementation of "Deep Learning-Enabled Semantic Communication Systems with Task-Unaware Transmitter and Dynamic Data"

License

Notifications You must be signed in to change notification settings

Hysome/Semantic-Communication-Systems

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

56 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Deep-Learning-Enabled-Semantic-Communication-Systems-with-Task-Unaware-Transmitter-and-Dynamic-Data

pytorch implementation of "Deep Learning-Enabled Semantic Communication Systems with Task-Unaware Transmitter and Dynamic Data"

Prerequites

  • [Python 3.7]
  • [PyTorch 0.1.12]
  • [Torchvision 0.9.1]
  • [Torch 1.5.1]
  • [Numpy 1.21.2]

The folders

"semantic_extraction" and "semantic_system_with_DA" are the semantic extraction part and the data adaptation part of the proposed method in the paper.

The details are represented in the two sub-folders.

Citation

Please use the following BibTeX citation if you use this repository in your work:

@article{Deep_semantic_comm_2022,
  title={Deep Learning-Enabled Semantic Communication Systems with Task-Unaware Transmitter and Dynamic Data},
  author={Zhang, Hongwei and Shao, Shuo and Tao, Meixia and Bi, Xiaoyan and Letaief, Khaled B},
  journal={arXiv preprint arXiv:2205.00271},
  year={2022}
}

About

pytorch implementation of "Deep Learning-Enabled Semantic Communication Systems with Task-Unaware Transmitter and Dynamic Data"

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 99.9%
  • Shell 0.1%