Deep JSCC

This implements training of deep JSCC models for wireless image transmission as described in the paper Deep Joint Source-Channel Coding for Wireless Image Transmission by Pytorch. And there has been a Tensorflow and keras implementations .

This is my first time to use PyTorch and git to reproduce a paper, so there may be some mistakes. If you find any, please let me know. Thanks!

Installation

conda or other virtual environment is recommended.

git clone https://github.com/chunbaobao/Deep-JSCC-PyTorch.git
pip install requirements.txt

Usage

Training Model

Run(example presented in paper)

cd ./Deep-JSCC-PyTorch

python train.py --lr 10e-4 --epochs 100 --batch_size 32 --channel 'AWGN' --saved ./saved --snr_list [1,4,7,13,19] --ratio_list [1/6,1/12] --dataset imagenet

python train.py --lr 10e-3 --epochs 100 --batch_size 64 --channel 'AWGN' --saved ./saved --snr_list [1,4,7,13,19] --ratio_list [1/6,1/12] --dataset cifar10

Evaluation

Citation

If you find (part of) this code useful for your research, please consider citing

@misc{chunhang_Deep-JSCC,
  author = {chunhang},
  title = {a pytorch implementation of Deep JSCC},
  url ={https://github.com/chunbaobao/Deep-JSCC-PyTorch},
  year = {2023}
}

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