jbdk24 / nelora-sensys

[SenSys 2021] "NELoRa: Towards Ultra-low SNR LoRa Communication with Neural-enhanced Demodulation" by Chenning Li, Hanqing Guo, Shuai Tong, Xiao Zeng, Zhichao Cao, Mi Zhang, Qiben Yan, Li Xiao, Jiliang Wang, Yunhao Liu

SenSys2021-NELoRa

This repository provides the codes for our SenSys 2021 paper

This repository contains scripts and instructions for reproducing the experiments in our SenSys '21 paper "NELoRa: Towards Ultra-low SNR LoRa Communication with Neural-enhanced Demodulation".

If you have any questions or comments, please post in the Issues on Github.

NELoRa won the Best Paper Award at SenSys '21!

This repo is actively maintained currently.

Illustrated in the following figure, our repo is composed of two modules, including the Symbol Generation and the neural-enhanced demodulation. Please find the dataset, instruction and source code of each module in the corresponding directory.

Notes

please consider to cite our paper if you use the code or data in your research project.

  @inproceedings{nelora2021sensys,
  	title={{NELoRa: Towards Ultra-low SNR LoRa Communication with Neural-enhanced Demodulation}},
  	author={Li, Chenning and Guo, Hanqing and Tong, Shuai and Zeng, Xiao and Cao, Zhichao and Zhang, Mi and Yan, Qiben and Xiao, Li and Wang, Jiliang and Liu, Yunhao},
    	booktitle={In Proceeding of ACM SenSys},
    	year={2021}
  }