PyTorch implementation of From Analog to Digital: Multi-Order Digital Joint Coding-Modulation for Semantic Communication
This repository is built upon NTSCC, thanks very much!
We would gradually upload the full-version of the implementation.
@ARTICLE{zhang2024MDJCM,
author={Zhang, Guangyi and Yang, Pujing and Cai, Yunlong and Hu, Qiyu and Yu, Guanding},
journal={IEEE Transactions on Communications},
title={From Analog to Digital: Multi-Order Digital Joint Coding-Modulation for Semantic Communication},
year={2024},
volume={},
number={},
pages={1-1},
doi={10.1109/TCOMM.2024.3511949}}Clone this repository and enter the directory using the commands below:
git clone https://github.com/zhang-guangyi/MDJCM.git
cd MDJCM/Python 3.9.12 is recommended.
Install the required packages with:
pip install -r requirements.txtIf you're having issues with installing PyTorch compatible with your CUDA version, we strongly recommend related documentation page (https://pytorch.org/get-started/previous-versions/).
- Download MDJCM-ckpt and put them into ./ckpt folder. This pretrained model is for MDJCM-A.
- Example of train the MDJCM-A model:
bash train.sh- Example of test the MDJCM-A model:
- Run test.sh
bash test.sh