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Pytorch implementation of the DeepSC

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Deep Learning Enabled Semantic Communication Systems

Huiqiang Xie, Zhijin Qin, Geoffrey Ye Li, and Biing-Hwang Juang

This is the implementation of Deep learning enabled semantic communication systems.

Requirements

  • See the requirements.txt for the required python packages and run pip install -r requirements.txt to install them.

Bibtex

@article{xie2021deep,
  author={H. {Xie} and Z. {Qin} and G. Y. {Li} and B. -H. {Juang}},
  journal={IEEE Transactions on Signal Processing}, 
  title={Deep Learning Enabled Semantic Communication Systems}, 
  year={2021},
  volume={Early Access}}

Preprocess

mkdir data
wget http://www.statmt.org/europarl/v7/europarl.tgz
tar zxvf europarl.tgz
python preprocess_text.py

Train

python main.py 

Notes

  • Please carefully set the $\lambda$ of mutual information part since I have tested the model in different platform, i.e., Tensorflow and Pytorch, same $\lambda$ shows different performance.

Evaluation

python performance.py

Notes

  • If you want to compute the sentence similarity, please download the bert model.

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Pytorch implementation of the DeepSC

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