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.

Citation

@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}}

Usage

Clone

Clone this repository and enter the directory using the commands below:

git clone https://github.com/zhang-guangyi/MDJCM.git
cd MDJCM/

Requirements

Python 3.9.12 is recommended.

Install the required packages with:

pip install -r requirements.txt

If 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/).

Pretrained Models

• Download MDJCM-ckpt and put them into ./ckpt folder. This pretrained model is for MDJCM-A.

Usage

1. Example of train the MDJCM-A model:

bash train.sh

2. Example of test the MDJCM-A model:

• Run test.sh

bash test.sh