Datasets and Code

Last updated:

We have made selected datasets and source code publicly available.

Radio-Frequency Fingerprint Identification (RFFI)

  1. 2024
    G. Shen, J. Zhang, A. Marshall, R. Woods, J. Cavallaro, and L. Chen, “Towards receiver-agnostic and collaborative radio frequency fingerprint identification,” IEEE Transactions on Mobile Computing, vol. 23, no. 7, pp. 7618–7634, 2024, doi: 10.1109/tmc.2023.3340039.
    DOI arXiv Code Data 
    @article{shen2023towards,
  title = {Towards receiver-agnostic and collaborative radio frequency fingerprint identification},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Woods, Roger and Cavallaro, Joseph and Chen, Liquan},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {23},
  number = {7},
  pages = {7618 - 7634},
  year = {2024},
  doi = {10.1109/tmc.2023.3340039},
  arxiv = {2207.02999},
  keywords = {rffi,lora, data_code}
}
  2. 2024
    G. Shen, J. Zhang, X. Wang, and S. Mao, “Federated Radio Frequency Fingerprint Identification Powered by Unsupervised Contrastive Learning,” IEEE Transactions on Information Forensics and Security, vol. 19, pp. 9204–9215, 2024, doi: 10.1109/tifs.2024.3469820.
    DOI Code Data 
    @article{shen2024federated,
  title = {Federated Radio Frequency Fingerprint Identification Powered by Unsupervised Contrastive Learning},
  author = {Shen, Guanxiong and Zhang, Junqing and Wang, Xuyu and Mao, Shiwen},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {19},
  pages = {9204 - 9215},
  year = {2024},
  doi = {10.1109/tifs.2024.3469820},
  keywords = {rffi, lora, data_code}
}
  3. 2023
    G. Shen, J. Zhang, A. Marshall, M. Valkama, and J. R. Cavallaro, “Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification,” IEEE Transactions on Information Forensics and Security, vol. 18, pp. 2355–2367, 2023, doi: 10.1109/tifs.2023.3266626.
    DOI arXiv Code Data 
    @article{shen2023length,
  title = {Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Valkama, Mikko and Cavallaro, Joseph R},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {18},
  pages = {2355 - 2367},
  year = {2023},
  doi = {10.1109/tifs.2023.3266626},
  arxiv = {2207.03001},
  keywords = {rffi,lora, data_code}
}
  4. 2022
    G. Shen, J. Zhang, A. Marshall, and J. R. Cavallaro, “Towards scalable and channel-robust radio frequency fingerprint identification for LoRa,” IEEE Transactions on Information Forensics and Security, vol. 17, pp. 774–787, 2022, doi: 10.1109/tifs.2022.3152404.
    DOI arXiv Code Data 
    @article{shen2022scalable,
  title = {Towards scalable and channel-robust radio frequency fingerprint identification for {LoRa}},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Cavallaro, Joseph R},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {17},
  pages = {774--787},
  year = {2022},
  doi = {10.1109/tifs.2022.3152404},
  arxiv = {2107.02867},
  keywords = {rffi,lora,data_code}
}

Physical-Layer Authentication

  1. 2025
    Y. Guo, J. Zhang, and Y.-W. P. Hong, “Practical Physical Layer Authentication for Mobile Scenarios Using a Synthetic Dataset Enhanced Deep Learning Approach,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 9305–9317, 2025, doi: 10.1109/tifs.2025.3602265.
    DOI arXiv Data 
    @article{guo2025practical,
  title = {Practical Physical Layer Authentication for Mobile Scenarios Using a Synthetic Dataset Enhanced Deep Learning Approach},
  author = {Guo, Yijia and Zhang, Junqing and Hong, Y-W Peter},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {9305 - 9317},
  year = {2025},
  doi = {10.1109/tifs.2025.3602265},
  arxiv = {2508.20861},
  keywords = {phy-auth, wifi, data_code}
}

Wi-Fi Sensing

  1. 2024
    G. Yin, J. Zhang, G. Shen, and Y. Chen, “FewSense, Towards a Scalable and Cross-Domain Wi-Fi Sensing System Using Few-Shot Learning,” IEEE Transactions on Mobile Computing, vol. 23, no. 1, pp. 453–468, 2024, doi: 10.1109/tmc.2022.3221902.
    DOI arXiv Code 
    @article{yin2022fewsense,
  title = {{FewSense}, Towards a Scalable and Cross-Domain {Wi-Fi} Sensing System Using Few-Shot Learning},
  author = {Yin, Guolin and Zhang, Junqing and Shen, Guanxiong and Chen, Yingying},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {23},
  number = {1},
  pages = {453 - 468},
  year = {2024},
  doi = {10.1109/tmc.2022.3221902},
  arxiv = {2203.02014},
  keywords = {wifi-sensing, data_code}
}