Publication (By Topics) - RFFI @ University of Liverpool

Survey/Tutorial

  1. 2025
    J. Zhang, F. Ardizzon, M. Piana, G. Shen, and S. Tomasin, “Physical Layer-Based Device Fingerprinting For Wireless Security: From Theory To Practice,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 5296–5325, 2025, doi: 10.1109/tifs.2025.3570118.
    DOI arXiv 
    @article{zhang2025physical,
  title = {Physical Layer-Based Device Fingerprinting For Wireless Security: From Theory To Practice},
  author = {Zhang, Junqing and Ardizzon, Francesco and Piana, Mattia and Shen, Guanxiong and Tomasin, Stefano},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {5296 - 5325},
  year = {2025},
  doi = {10.1109/tifs.2025.3570118},
  arxiv = {2506.09807},
  keywords = {rffi,phy-auth,survey}
}
  2. 2024
    L. Xie, L. Peng, J. Zhang, and A. Hu, “Radio frequency fingerprint identification for Internet of Things: A survey,” Security and Safety, vol. 3, p. 2023022, 2024, doi: 10.1051/sands/2023022.
    DOI 
    @article{xie2024radio,
  title = {Radio frequency fingerprint identification for Internet of Things: A survey},
  author = {Xie, Lingnan and Peng, Linning and Zhang, Junqing and Hu, Aiqun},
  journal = {Security and Safety},
  volume = {3},
  pages = {2023022},
  year = {2024},
  doi = {10.1051/sands/2023022},
  publisher = {EDP Sciences and CSPM},
  keywords = {rffi,survey}
}
  3. 2023
    J. Zhang, G. Shen, W. Saad, and K. Chowdhury, “Radio frequency fingerprint identification for device authentication in the internet of things,” IEEE Communications Magazine, vol. 61, no. 10, pp. 110–115, 2023, doi: 10.1109/mcom.003.2200974.
    DOI 
    @article{zhang2023radio,
  title = {Radio frequency fingerprint identification for device authentication in the internet of things},
  author = {Zhang, Junqing and Shen, Guanxiong and Saad, Walid and Chowdhury, Kaushik},
  journal = {IEEE Communications Magazine},
  volume = {61},
  number = {10},
  pages = {110 - 115},
  year = {2023},
  doi = {10.1109/mcom.003.2200974},
  keywords = {rffi,survey}
}
  4. 2023
    G. Shen, J. Zhang, and A. Marshall, “Deep learning-powered radio frequency fingerprint identification: Methodology and case study,” IEEE Communications Magazine, vol. 61, no. 9, pp. 170–176, 2023, doi: 10.1109/mcom.001.2200695.
    DOI 
    @article{shen2023deep,
  title = {Deep learning-powered radio frequency fingerprint identification: Methodology and case study},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan},
  journal = {IEEE Communications Magazine},
  volume = {61},
  number = {9},
  pages = {170 - 176},
  year = {2023},
  doi = {10.1109/mcom.001.2200695},
  keywords = {rffi,survey}
}
  5. 2022
    J. Zhang, C.-H. Chang, C. Gu, and L. Hanzo, “Radio Frequency Fingerprints vs. Physical Unclonable Functions-Are They Twins, Competitors or Allies?,” IEEE Network, vol. 36, no. 6, pp. 68–75, 2022, doi: 10.1109/mnet.107.2100372.
    DOI 
    @article{zhang2022radio,
  title = {Radio Frequency Fingerprints vs. Physical Unclonable Functions-Are They Twins, Competitors or Allies?},
  author = {Zhang, Junqing and Chang, Chip-Hong and Gu, Chongyan and Hanzo, Lajos},
  journal = {IEEE Network},
  volume = {36},
  number = {6},
  pages = {68 - 75},
  year = {2022},
  doi = {10.1109/mnet.107.2100372},
  keywords = {rffi,survey}
}
  6. 2019
    J. Zhang, S. Rajendran, Z. Sun, R. Woods, and L. Hanzo, “Physical layer security for the Internet of Things: Authentication and key generation,” IEEE Wireless Communications, vol. 26, no. 5, pp. 92–98, 2019, doi: 10.1109/mwc.2019.1800455.
    DOI 
    @article{zhang2019physical,
  title = {Physical layer security for the {Internet} of Things: Authentication and key generation},
  author = {Zhang, Junqing and Rajendran, Sekhar and Sun, Zhi and Woods, Roger and Hanzo, Lajos},
  journal = {IEEE Wireless Communications},
  volume = {26},
  number = {5},
  pages = {92--98},
  year = {2019},
  doi = {10.1109/mwc.2019.1800455},
  keywords = {rffi,keygen,survey}
}

Wi-Fi RFFI

Refereed Jounal Articles

  1. 2026
    L. Xie, L. Peng, and J. Zhang, “Toward Channel-Robust RF Fingerprint Identification Using Spectrum Averaging and High-Order Difference,” IEEE Transactions on Information Forensics and Security, vol. 21, pp. 6727–6742, 2026, doi: 10.1109/TIFS.2026.3714140.
    DOI 
    @article{xie2026toward,
  title = {Toward Channel-Robust {RF} Fingerprint Identification Using Spectrum Averaging and High-Order Difference},
  author = {Xie, Lingnan and Peng, Linning and Zhang, Junqing},
  journal = {IEEE Transactions on Information Forensics and Security},
  year = {2026},
  publisher = {IEEE},
  volume = {21},
  pages = {6727 - 6742},
  doi = {10.1109/TIFS.2026.3714140},
  keywords = {rffi,wifi}
}
  2. 2025
    L. Xie, L. Peng, J. Zhang, A. Gao, H. Fu, and J. Shi, “Channel2Channel: Towards Robust Radio Frequency Fingerprint Extraction and Identification,” IEEE Journal on Selected Areas in Communications, vol. 43, no. 11, pp. 3737–3751, 2025, doi: 10.1109/jsac.2025.3584434.
    DOI 
    @article{xie2025channel2channel,
  title = {Channel2Channel: Towards Robust Radio Frequency Fingerprint Extraction and Identification},
  author = {Xie, Lingnan and Peng, Linning and Zhang, Junqing and Gao, Ang and Fu, Hua and Shi, Junxian},
  journal = {IEEE Journal on Selected Areas in Communications},
  volume = {43},
  number = {11},
  pages = {3737 - 3751},
  year = {2025},
  doi = {10.1109/jsac.2025.3584434},
  keywords = {rffi, wifi}
}
  3. 2023
    Y. Xing, A. Hu, J. Zhang, L. Peng, and X. Wang, “Design of A Channel Robust Radio Frequency Fingerprint Identification Scheme,” IEEE Internet of Things Journal, vol. 10, no. 8, pp. 6946–6959, 2023, doi: 10.1109/jiot.2022.3228280.
    DOI 
    @article{xing2023design,
  title = {Design of A Channel Robust Radio Frequency Fingerprint Identification Scheme},
  author = {Xing, Yuexiu and Hu, Aiqun and Zhang, Junqing and Peng, Linning and Wang, Xianbin},
  journal = {IEEE Internet of Things Journal},
  volume = {10},
  number = {8},
  pages = {6946 - 6959},
  year = {2023},
  doi = {10.1109/jiot.2022.3228280},
  keywords = {rffi,wifi}
}

Refereed Conference Proceedings

  1. 2025
    L. Xie, L. Peng, and J. Zhang, “Towards Robust RF Fingerprint Identification Using Spectral Regrowth and Carrier Frequency Offset,” in Proc. IEEE Conference on Computer Communications (INFOCOM), 2025, pp. 1–10. doi: 10.1109/infocom55648.2025.11044651.
    DOI arXiv 
    @inproceedings{xie2024towards,
  title = {Towards Robust {RF} Fingerprint Identification Using Spectral Regrowth and Carrier Frequency Offset},
  author = {Xie, Lingnan and Peng, Linning and Zhang, Junqing},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM)},
  pages = {1--10},
  year = {2025},
  doi = {10.1109/infocom55648.2025.11044651},
  arxiv = {2412.07269},
  keywords = {rffi,wifi}
}
  2. 2025
    G. Yin, J. Zhang, Y. Ding, and S. Cotton, “Noise-Robust Radio Frequency Fingerprint Identification Using Denoise Diffusion Model,” in Proc. IEEE Wireless Communications and Networking Conference Workshops, 2025, pp. 1–6. doi: 10.1109/wcnc61545.2025.10978824.
    DOI arXiv 
    @inproceedings{yin2025noise,
  title = {Noise-Robust Radio Frequency Fingerprint Identification Using Denoise Diffusion Model},
  author = {Yin, Guolin and Zhang, Junqing and Ding, Yuan and Cotton, Simon},
  booktitle = {Proc. IEEE  Wireless Communications and Networking Conference Workshops},
  pages = {1--6},
  year = {2025},
  doi = {10.1109/wcnc61545.2025.10978824},
  arxiv = {2503.05514},
  keywords = {rffi,wifi}
}

LoRa RFFI

Refereed Jounal Articles

  1. 2026
    J. Ma, J. Zhang, G. Shen, A. Marshall, and C.-H. Chang, “Adversarial Attacks Against Deep Learning-Based Radio Frequency Fingerprint Identification,” IEEE Transactions on Mobile Computing, vol. 25, no. 6, pp. 7831–7844, 2026, doi: 10.1109/tmc.2025.3646257.
    DOI arXiv 
    @article{ma2025adversarial,
  title = {Adversarial Attacks Against Deep Learning-Based Radio Frequency Fingerprint Identification},
  author = {Ma, Jie and Zhang, Junqing and Shen, Guanxiong and Marshall, Alan and Chang, Chip-Hong},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {25},
  number = {6},
  pages = {7831--7844},
  year = {2026},
  doi = {10.1109/tmc.2025.3646257},
  arxiv = {2512.12002},
  keywords = {rffi, lora}
}
  2. 2025
    J. Ma, J. Zhang, G. Shen, L. Peng, and A. Marshall, “Towards Channel-Robust and Receiver-Independent Radio Frequency Fingerprint Identification,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 12112–12125, 2025, doi: 10.1109/tifs.2025.3630316.
    DOI arXiv 
    @article{ma2025tifs,
  title = {Towards Channel-Robust and Receiver-Independent Radio Frequency Fingerprint Identification},
  author = {Ma, Jie and Zhang, Junqing and Shen, Guanxiong and Peng, Linning and Marshall, Alan},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {12112 - 12125},
  year = {2025},
  doi = {10.1109/tifs.2025.3630316},
  arxiv = {2512.12070},
  keywords = {rffi,lora}
}
  3. 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}
}
  4. 2024
    G. Shen and J. Zhang, “Exploration of transferable deep learning-aided radio frequency fingerprint identification systems,” Security and Safety, vol. 3, p. 2023019, 2024, doi: 10.1051/sands/2023019.
    DOI 
    @article{shen2024exploration,
  title = {Exploration of transferable deep learning-aided radio frequency fingerprint identification systems},
  author = {Shen, Guanxiong and Zhang, Junqing},
  journal = {Security and Safety},
  volume = {3},
  pages = {2023019},
  year = {2024},
  doi = {10.1051/sands/2023019},
  publisher = {EDP Sciences and CSPM},
  keywords = {rffi,lora}
}
  5. 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}
}
  6. 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}
}
  7. 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}
}
  8. 2021
    G. Shen, J. Zhang, A. Marshall, L. Peng, and X. Wang, “Radio frequency fingerprint identification for LoRa using deep learning,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 8, pp. 2604–2616, 2021, doi: 10.1109/jsac.2021.3087250.
    DOI 
    @article{shen2021radioj,
  title = {Radio frequency fingerprint identification for {LoRa} using deep learning},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Peng, Linning and Wang, Xianbin},
  journal = {IEEE Journal on Selected Areas in Communications},
  volume = {39},
  number = {8},
  pages = {2604--2616},
  year = {2021},
  doi = {10.1109/jsac.2021.3087250},
  keywords = {rffi,lora}
}

Refereed Conference Proceedings

  1. 2026
    S. Wang, J. Zhang, J. Mao, A. Brighente, G. Shen, and M. Conti, “Triad-GAN: Feature-Level Generative Adversarial Network for Multi-Receiver Radio Frequency Fingerprint Identification,” in Proc. IEEE International Conference on Communications (ICC), 2026, p. 88052.
    @inproceedings{wang2026triad,
  title = {{Triad-GAN}: Feature-Level Generative Adversarial Network for Multi-Receiver Radio Frequency Fingerprint Identification},
  author = {Wang, Shuo and Zhang, Junqing and Mao, Jiahuai and Brighente, Alessandro and Shen, Guanxiong and Conti, Mauro},
  booktitle = {Proc. IEEE International Conference on Communications (ICC)},
  pages = {88052},
  year = {2026},
  keywords = {rffi,lora}
}
  2. 2026
    E. Bothereau et al., “Lightweight Preprocessing and Feature Extraction for LoRa RF Fingerprint Identification,” in Proc. IEEE International Conference on Communications (ICC), IEEE, 2026, pp. 1–6.
    @inproceedings{bothereau2026lightweight,
  title = {Lightweight Preprocessing and Feature Extraction for {LoRa RF} Fingerprint Identification},
  author = {Bothereau, Emma and Gerzaguet, Robin and Gautier, Matthieu and Zhang, Junqing and Chillet, Alice and Marshall, Alan and Berder, Olivier},
  booktitle = {Proc. IEEE International Conference on Communications (ICC)},
  pages = {1--6},
  year = {2026},
  organization = {IEEE},
  keywords = {rffi,lora}
}
  3. 2025
    J. Ma, J. Zhang, G. Shen, L. Peng, and A. Marshall, “Towards Channel-Robust Radio Frequency Fingerprint Identification Using Contrastive Learning,” in Proc. IEEE Wireless Communications and Networking Conference, 2025, pp. 1–6. doi: 10.1109/wcnc61545.2025.10978330.
    DOI 
    @inproceedings{ma2025towards,
  title = {Towards Channel-Robust Radio Frequency Fingerprint Identification Using Contrastive Learning},
  author = {Ma, Jie and Zhang, Junqing and Shen, Guanxiong and Peng, Linning and Marshall, Alan},
  booktitle = {Proc. IEEE  Wireless Communications and Networking Conference},
  pages = {1--6},
  year = {2025},
  doi = {10.1109/wcnc61545.2025.10978330},
  keywords = {rffi,lora}
}
  4. 2024
    T. T. An, S. L. Cotton, J. Zhang, Y. Ding, and T. Q. Duong, “LoRa Radio Frequency Fingerprinting Using a Hybrid Quantum-Classical Neural Network,” in Proc. IEEE 100th Vehicular Technology Conference, 2024.
    @inproceedings{an2024lora,
  title = {{LoRa} Radio Frequency Fingerprinting Using a Hybrid Quantum-Classical Neural Network},
  author = {An, To Truong and Cotton, Simon L and Zhang, Junqing and Ding, Yuan and Duong, Trung Q},
  booktitle = {Proc. IEEE 100th Vehicular Technology Conference},
  year = {2024},
  keywords = {rffi,lora}
}
  5. 2023
    J. Ma, J. Zhang, G. Shen, A. Marshall, and C.-H. Chang, “White-Box Adversarial Attacks on Deep Learning-Based Radio Frequency Fingerprint Identification,” in Proc. IEEE ICC, 2023, pp. 3714–3719. doi: 10.1109/icc45041.2023.10278927.
    DOI arXiv 
    @inproceedings{ma2023whitebox,
  title = {White-Box Adversarial Attacks on Deep Learning-Based Radio Frequency Fingerprint Identification},
  author = {Ma, Jie and Zhang, Junqing and Shen, Guanxiong and Marshall, Alan and Chang, Chip-Hong},
  booktitle = {Proc. IEEE ICC},
  pages = {3714--3719},
  year = {2023},
  doi = {10.1109/icc45041.2023.10278927},
  arxiv = {2308.07433},
  keywords = {rffi,lora}
}
  6. 2021
    G. Shen, J. Zhang, A. Marshall, L. Peng, and X. Wang, “Radio frequency fingerprint identification for LoRa using spectrogram and CNN,” in Proc. IEEE Conference on Computer Communications (INFOCOM), IEEE, 2021, pp. 1–10. doi: 10.1109/infocom42981.2021.9488793.
    DOI arXiv 
    @inproceedings{shen2021infocom,
  title = {Radio frequency fingerprint identification for LoRa using spectrogram and {CNN}},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Peng, Linning and Wang, Xianbin},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM)},
  pages = {1--10},
  year = {2021},
  doi = {10.1109/infocom42981.2021.9488793},
  arxiv = {2101.01668},
  organization = {IEEE},
  keywords = {rffi,lora}
}
  7. 2021
    G. Shen, J. Zhang, A. Marshall, M. Valkama, and J. Cavallaro, “Radio Frequency Fingerprint Identification for Security in Low-Cost IoT Devices,” in Proc. 55th Asilomar Conference on Signals, Systems, and Computers, 2021, pp. 309–313. doi: 10.1109/ieeeconf53345.2021.9723287.
    DOI arXiv 
    @inproceedings{shen2021asiloma,
  title = {Radio Frequency Fingerprint Identification for Security in Low-Cost {IoT} Devices},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Valkama, Mikko and Cavallaro, Joseph},
  booktitle = {Proc. 55th Asilomar Conference on Signals, Systems, and Computers},
  pages = {309--313},
  year = {2021},
  doi = {10.1109/ieeeconf53345.2021.9723287},
  arxiv = {2111.14275},
  keywords = {rffi,lora}
}

BLE RFFI

Refereed Jounal Articles

    Refereed Conference Proceedings

    1. 2025
      N. Yuan, J. Zhang, Y. Ding, and S. L. Cotton, “Robust Radio Frequency Fingerprint Identification for Bluetooth Low Energy under Low SNR and Channel Variations,” in Proc. IEEE Wireless Communications and Networking Conference, 2025, pp. 01–06. doi: 10.1109/wcnc61545.2025.10978258.
      DOI 
      @inproceedings{yuan2025robust,
  title = {Robust Radio Frequency Fingerprint Identification for {Bluetooth} Low Energy under Low SNR and Channel Variations},
  author = {Yuan, Ningze and Zhang, Junqing and Ding, Yuan and Cotton, Simon L},
  booktitle = {Proc. IEEE Wireless Communications and Networking Conference},
  pages = {01--06},
  year = {2025},
  doi = {10.1109/wcnc61545.2025.10978258},
  keywords = {rffi,ble}
}

    ZigBee RFFI

    Refereed Jounal Articles

    1. 2020
      L. Peng, J. Zhang, M. Liu, and A. Hu, “Deep learning based RF fingerprint identification using differential constellation trace figure,” IEEE Transactions on Vehicular Technology, vol. 69, no. 1, pp. 1091–1095, 2020, doi: 10.1109/tvt.2019.2950670.
      DOI 
      @article{peng2019deep,
  title = {Deep learning based {RF} fingerprint identification using differential constellation trace figure},
  author = {Peng, Linning and Zhang, Junqing and Liu, Ming and Hu, Aiqun},
  journal = {IEEE Transactions on Vehicular Technology},
  volume = {69},
  number = {1},
  pages = {1091--1095},
  year = {2020},
  doi = {10.1109/tvt.2019.2950670},
  keywords = {rffi,zigbee}
}
    2. 2019
      L. Peng, A. Hu, J. Zhang, Y. Jiang, J. Yu, and Y. Yan, “Design of a hybrid RF fingerprint extraction and device classification scheme,” IEEE Internet of Things Journal, vol. 6, no. 1, pp. 349–360, 2019, doi: 10.1109/jiot.2018.2838071.
      DOI 
      @article{peng2018design,
  title = {Design of a hybrid {RF} fingerprint extraction and device classification scheme},
  author = {Peng, Linning and Hu, Aiqun and Zhang, Junqing and Jiang, Yu and Yu, Jiabao and Yan, Yan},
  journal = {IEEE Internet of Things Journal},
  volume = {6},
  number = {1},
  pages = {349--360},
  year = {2019},
  doi = {10.1109/jiot.2018.2838071},
  keywords = {rffi,,zigbee}
}
    3. 2018
      Y. Xing, A. Hu, J. Zhang, L. Peng, and G. Li, “On radio frequency fingerprint identification for DSSS systems in low SNR scenarios,” IEEE Communications Letters, vol. 22, no. 11, pp. 2326–2329, 2018, doi: 10.1109/lcomm.2018.2871454.
      DOI 
      @article{xing2018radio,
  title = {On radio frequency fingerprint identification for {DSSS} systems in low {SNR} scenarios},
  author = {Xing, Yuexiu and Hu, Aiqun and Zhang, Junqing and Peng, Linning and Li, Guyue},
  journal = {IEEE Communications Letters},
  volume = {22},
  number = {11},
  pages = {2326--2329},
  year = {2018},
  doi = {10.1109/lcomm.2018.2871454},
  keywords = {rffi,zigbee}
}

    Refereed Conference Proceedings

    1. 2023
      Y. Xing, X. Chen, J. Zhang, A. Hu, and D. Zhang, “A Noise-Robust Radio Frequency Fingerprint Identification Scheme for Internet of Things Devices,” in Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops, 2023, pp. 1–6. doi: 10.1109/infocomwkshps57453.2023.10225749.
      DOI 
      @inproceedings{xing2023noise,
  title = {A Noise-Robust Radio Frequency Fingerprint Identification Scheme for Internet of Things Devices},
  author = {Xing, Yuexiu and Chen, Xiaoxing and Zhang, Junqing and Hu, Aiqun and Zhang, Dengyin},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops},
  pages = {1--6},
  year = {2023},
  doi = {10.1109/infocomwkshps57453.2023.10225749},
  keywords = {rffi,zigbee}
}

    LTE RFFI

    Refereed Jounal Articles

    1. 2024
      L. Peng, Z. Wu, J. Zhang, M. Liu, H. Fu, and A. Hu, “Hybrid RFF Identification for LTE Using Wavelet Coefficient Graph and Differential Spectrum,” IEEE Transactions on Vehicular Technology, vol. 73, no. 8, pp. 11621–11636, 2024, doi: 10.1109/tvt.2024.3380671.
      DOI 
      @article{peng2024hybrid,
  title = {Hybrid {RFF} Identification for {LTE} Using Wavelet Coefficient Graph and Differential Spectrum},
  author = {Peng, Linning and Wu, Zhenni and Zhang, Junqing and Liu, Ming and Fu, Hua and Hu, Aiqun},
  journal = {IEEE Transactions on Vehicular Technology},
  volume = {73},
  number = {8},
  pages = {11621 - 11636},
  year = {2024},
  doi = {10.1109/tvt.2024.3380671},
  keywords = {rffi,lte}
}
    2. 2024
      P. Yin et al., “Multi-Channel CNN-Based Open-Set RF Fingerprint Identification for LTE Devices,” IEEE Transactions on Cognitive Communications and Networking, vol. 10, no. 5, pp. 1788–1800, 2024, doi: 10.1109/tccn.2024.3391293.
      DOI 
      @article{yin2024multi,
  title = {Multi-Channel {CNN}-Based Open-Set {RF} Fingerprint Identification for {LTE} Devices},
  author = {Yin, Pengcheng and Peng, Linning and Shen, Guanxiong and Zhang, Junqing and Liu, Ming and Fu, Hua and Hu, Aiqun and Wang, Xianbin},
  journal = {IEEE Transactions on Cognitive Communications and Networking},
  volume = {10},
  number = {5},
  pages = {1788 - 1800},
  year = {2024},
  doi = {10.1109/tccn.2024.3391293},
  keywords = {rffi,lte}
}

    Refereed Conference Proceedings

    1. 2024
      M. Wang, L. Peng, L. Xie, J. Zhang, M. Liu, and H. Fu, “Design of Noise Robust Open-Set Radio Frequency Fingerprint Identification Method,” in Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops, 2024, pp. 1–6. doi: 10.1109/infocomwkshps61880.2024.10620671.
      DOI 
      @inproceedings{wang2024design,
  title = {Design of Noise Robust Open-Set Radio Frequency Fingerprint Identification Method},
  author = {Wang, Min and Peng, Linning and Xie, Lingnan and Zhang, Junqing and Liu, Ming and Fu, Hua},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops},
  pages = {1--6},
  year = {2024},
  doi = {10.1109/infocomwkshps61880.2024.10620671},
  keywords = {rffi,lte}
}
    2. 2022
      Z. Wu, L. Peng, J. Zhang, M. Liu, H. Fu, and A. Hu, “Authorized and Rogue LTE Terminal Identification Using Wavelet Coefficient Graph with Auto-encoder,” in Proc. IEEE VTC Fall, 2022, pp. 1–5. doi: 10.1109/vtc2022-fall57202.2022.10012861.
      DOI 
      @inproceedings{wu2022authorized,
  title = {Authorized and Rogue {LTE} Terminal Identification Using Wavelet Coefficient Graph with Auto-encoder},
  author = {Wu, Zhenni and Peng, Linning and Zhang, Junqing and Liu, Ming and Fu, Hua and Hu, Aiqun},
  booktitle = {Proc. IEEE VTC Fall},
  pages = {1--5},
  year = {2022},
  doi = {10.1109/vtc2022-fall57202.2022.10012861},
  keywords = {rffi,lte}
}
    3. 2022
      Y. Qiu, L. Peng, J. Zhang, M. Liu, H. Fu, and A. Hu, “Signal-independent RFF Identification for LTE Mobile Devices via Ensemble Deep Learning,” in Proc. IEEE GLOBECOM, 2022, pp. 37–42. doi: 10.1109/globecom48099.2022.10000722.
      DOI 
      @inproceedings{qiu2022signal,
  title = {Signal-independent {RFF} Identification for {LTE} Mobile Devices via Ensemble Deep Learning},
  author = {Qiu, Yanjin and Peng, Linning and Zhang, Junqing and Liu, Ming and Fu, Hua and Hu, Aiqun},
  booktitle = {Proc. IEEE GLOBECOM},
  pages = {37--42},
  year = {2022},
  doi = {10.1109/globecom48099.2022.10000722},
  keywords = {rffi,lte}
}
    4. 2021
      P. Yin, L. Peng, J. Zhang, M. Liu, H. Fu, and A. Hu, “LTE Device Identification Based on RF Fingerprint with Multi-Channel Convolutional Neural Network,” in Proc. IEEE GLOBECOM), 2021, pp. 1–6. doi: 10.1109/globecom46510.2021.9685067.
      DOI 
      @inproceedings{yin2021lte,
  title = {{LTE} Device Identification Based on {RF} Fingerprint with Multi-Channel Convolutional Neural Network},
  author = {Yin, Pengcheng and Peng, Linning and Zhang, Junqing and Liu, Ming and Fu, Hua and Hu, Aiqun},
  booktitle = {Proc. IEEE GLOBECOM)},
  pages = {1--6},
  year = {2021},
  doi = {10.1109/globecom46510.2021.9685067},
  keywords = {rffi,lte}
}

    Power Amplifier

    Journal

    1. Yuepei Li, Symon K. Podilchak, Junqing Zhang, Simon L. Cotton, Tharmalingam Ratnarajah, and Yuan Ding, “RFFI Protocols Using Antenna Mutual Coupling and Power Amplifier Nonlinear Memory Effects,” IEEE Communications Letters, vol. 29, no. 6, pp. 1250 - 1254, Jun. 2025. IEEE
    2. Yuepei Li, Kai Xu, Junqing Zhang, Chongyan Gu, Yuan Ding, George Goussetis, and Symon K. Podilchak, “PUF-Assisted Radio Frequency Fingerprinting Exploiting Power Amplifier Active Load-pulling”, IEEE Transactions on Information Forensics and Security, vol. 19, pp. 5015 - 5029, 2024. IEEE Xplore
    3. Yuepei Li, Yuan Ding, Junqing Zhang, George Goussetis, and Symon K. Podilchak, “Radio Frequency Fingerprinting Exploiting Non-Linear Memory Effect,” IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 4, pp. 1618 - 1631, Dec. 2022. IEEE Xplore

    Conference

    1. Yuepei Li, Yuan Ding, George Goussetis, and Junqing Zhang, “Power Amplifier enabled RF Fingerprint Identification,” in Proc. IEEE Texas Symposium on Wireless and Microwave Circuits and Systems, 2021.

    Attack

    Journal

    1. Jie Ma, Junqing Zhang, Guanxiong Shen, Alan Marshall, and Chip-Hong Chang “Adversarial Attacks Against Deep Learning-Based Radio Frequency Fingerprint Identification,” IEEE Transactions on Mobile Computing, vol. 25, no. 6, pp. 7831 - 7844, 2026. IEEE, arXiv link.
    2. Tianya Zhao, Junqing Zhang, Jun Dai, Xiaoyan Sun, and Xuyu Wang, “Unveiling the Threat: Data-Free Backdoor Attacks on PreTrained Models for RF Fingerprinting,” IEEE Transactions on Mobile Computing, vol. 25, no. 4, pp. 5421 - 5433, 2026. IEEE
    3. Tianya Zhao, Junqing Zhang, Shiwen Mao, and Xuyu Wang, “Explanation-Guided Backdoor Attacks Against Model-Agnostic RF Fingerprinting Systems,” IEEE Transactions on Mobile Computing, vol. 24, no. 3, pp. 2029 - 2042, Mar. 2025. IEEE

    Conference

    1. Tianya Zhao, Ningning Wang, Junqing Zhang, and Xuyu Wang, “Protocol-agnostic and Data-free Backdoor Attacks on Pre-trained Models in RF Fingerprinting”, in Proc. IEEE INFOCOM, 2025.
    2. Tianya Zhao, Xuyu Wang, Junqing Zhang, and Shiwen Mao, “Explanation-Guided Backdoor Attacks on Model-Agnostic RF Fingerprinting,” in Proc. IEEE INFOCOM, 2024.
    3. Jie Ma, Junqing Zhang, Guanxiong Shen, Alan Marshall, and Chip-Hong Chang, “White-Box Adversarial Attacks on Deep Learning-Based Radio Frequency Fingerprint Identification”, in Proc. IEEE ICC, 2023
    4. Yuxuan Xu, Ming Liu, Linning Peng, Junqing Zhang, and Yawen Zheng, “Colluding RF Fingerprint Impersonation Attack Based on Generative Adversarial Network”, in Proc. IEEE ICC, 2022

    Modelling

    1. 2021
      J. Zhang, R. Woods, M. Sandell, M. Valkama, A. Marshall, and J. Cavallaro, “Radio frequency fingerprint identification for narrowband systems, Modelling and classification,” IEEE Transactions on Information Forensics and Security, vol. 16, pp. 3974–3987, 2021, doi: 10.1109/tifs.2021.3088008.
      DOI 
      @article{zhang2021radio,
  title = {Radio frequency fingerprint identification for narrowband systems, Modelling and classification},
  author = {Zhang, Junqing and Woods, Roger and Sandell, Magnus and Valkama, Mikko and Marshall, Alan and Cavallaro, Joseph},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {16},
  pages = {3974--3987},
  year = {2021},
  doi = {10.1109/tifs.2021.3088008},
  keywords = {rffi}
}

    Others

    Journal Article

    1. 2020
      Y. Xing, A. Hu, J. Zhang, J. Yu, G. Li, and T. Wang, “Design of a robust radio-frequency fingerprint identification scheme for multimode LFM radar,” IEEE Internet of Things Journal, vol. 7, no. 10, pp. 10581–10593, 2020, doi: 10.1109/jiot.2020.3003692.
      DOI 
      @article{xing2020design,
  title = {Design of a robust radio-frequency fingerprint identification scheme for multimode {LFM} radar},
  author = {Xing, Yuexiu and Hu, Aiqun and Zhang, Junqing and Yu, Jiabao and Li, Guyue and Wang, Ting},
  journal = {IEEE Internet of Things Journal},
  volume = {7},
  number = {10},
  pages = {10581--10593},
  year = {2020},
  doi = {10.1109/jiot.2020.3003692},
  keywords = {rffi}
}

    Conference Paper

    1. To Truong An, Simon L. Cotton, Junqing Zhang, Yuan Ding and Trung Q. Duong, “LoRa Radio Frequency Fingerprinting Using a Hybrid Quantum-Classical Neural Network”, in Proc. IEEE VTC Fall, 2024.
    2. Chuanting Zhang, Shuping Dang, Junqing Zhang, Haixia Zhang, and Mark A. Beach, “Federated Radio Frequency Fingerprinting with Model Transfer and Adaptation”, in Proc. IEEE INFOCOM Workshop, 2023. arXiv
    3. Hongyi Luo, Guyue Li, Yuexiu Xing, Junqing Zhang, Aiqun Hu, and Xianbin Wang, “RelativeRFF: Multi-Antenna Device Identification in Multipath Propagation Scenarios”, in Proc. IEEE ICC, 2023