Python code for "Joint coding-modulation for digital semantic communications via variational autoencoder"

This repository contains the original code and models for the work Joint Coding-Modulation for Digital Semantic Communications via Variational Autoencoder[1].

[1] Y. Bo, Y. Duan, S. Shao and M. Tao, "Joint Coding-Modulation for Digital Semantic Communications via Variational Autoencoder," in IEEE Transactions on Communications, doi: 10.1109/TCOMM.2024.3386577.

Requirements

• matplotlib==3.7.2
• numpy==1.23.5
• pandas==2.0.3
• scikit_learn==1.3.0
• scipy==1.13.0
• scikit-image==0.21.0
• torch==1.12.1+cu113
• torchvision==0.13.1+cu113
• tqdm==4.65.0

Training & Evaluation

This code implements 4 modulation schemes: BPSK, 4QAM, 16QAM and 64QAM.

For training, run the following command (as an example):

python main.py --mode 'train' --mod_method '64qam' --load_checkpoint 1

For evaluation, run the following command (as an example):

python main.py --mode 'test' --mod_method '64qam' --load_checkpoint 1