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Semantic Communications for Wireless Sensing: RIS-aided Encoding and Self-supervised Decoding

This repository hosts a demonstration of the encoder and decoder algorithm as presented in the paper "Semantic Communications for Wireless Sensing: RIS-aided Encoding and Self-supervised Decoding" by Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Junshan Zhang, Xuemin (Sherman) Shen, accepted by IEEE JSAC.

The paper can be found Here.

System Model

🔧 Environment Setup

To create a new conda environment, execute the following command:

conda create --name invsems python==3.8

⚡Activate Environment

Activate the created environment with:

conda activate invsems

📦 Install Required Packages

The following packages can be installed using pip:

pip install numpy
pip install scipy
pip install scikit-image
pip install torch
pip install torchvision
pip install opencv-python
pip install tqdm

Please pay attention to the torch version, according to your CUDA version. Refer to here.

🏃‍♀️ Run the Program

Set the created env as the runing env.

Run main.py to start the program.

🔍 Check the results

In this demo, we consider the encoding and decoing of wireless signal amplitude information as:

With the decoding process going, the results will be recorded: Set Pycharm

Set Pycharm

After 2 decoding steps, the result is not good: Set Pycharm

After 16 decoding steps, the result is quite good: Set Pycharm

Citation

@article{du2023semantic,
  title={Semantic communications for wireless sensing: RIS-aided encoding and self-supervised decoding},
  author={Du, Hongyang and Wang, Jiacheng and Niyato, Dusit and Kang, Jiawen and Xiong, Zehui and Zhang, Junshan and Shen, Xuemin},
  journal={IEEE Journal on Selected Areas in Communications},
  year={2023},
  publisher={IEEE}
}

📚 Acknowledgement

As we claimed in our paper, this repository used the codes in the following papers:

PnP-DIP: https://github.com/mengziyi64/CASSI-Self-Supervised
Deep Image Priors: https://github.com/zhaodongsun/pnp_dip
LRS-PnP-DIP: https://github.com/shuoli0708/LRS-PnP-DIP

Please consider to cite these papers if their codes are used in your research.