We have made selected datasets and source code publicly available.
Radio-Frequency Fingerprint Identification (RFFI)
1. Guanxiong Shen, **Junqing Zhang**, Xuyu Wang, and Shiwen Mao, “Federated Radio Frequency Fingerprint Identification Powered by Unsupervised Contrastive Learning,” _IEEE Transactions on Information Forensics and Security_, vol. 19, pp. 9204-9215, 2024. [IEEE Xplore](https://ieeexplore.ieee.org/document/10697226){:target="_blank"}
* [Dataset: LoRa Federated RFFI](https://ieee-dataport.org/documents/lorafederatedrffidataset){:target="_blank"}
* [Code: LoRa Federated RFFI](https://github.com/gxhen/federatedRFFI){:target="_blank"}
1. Guanxiong Shen, **Junqing Zhang***, Alan Marshall, Roger Woods, Joseph Cavallaro, and Liquan Chen, “Towards Receiver-Agnostic and Collaborative Radio Frequency Fingerprint Identification”, _IEEE Transactions on Mobile Computing_, vol. 23, no. 7, pp. 7618 - 7634, Jul. 2024. [IEEE](https://ieeexplore.ieee.org/document/10345732){:target="_blank"}, [arXiv link](https://arxiv.org/abs/2207.02999){:target="_blank"}
* [Dataset: Radio Frequency Fingerprint LoRa Dataset Multiple Receivers](https://ieee-dataport.org/documents/radio-frequency-fingerprint-lora-dataset-multiple-receivers){:target="_blank"}
* [Code: Radio Frequency Fingerprint LoRa Dataset Multiple Receivers](https://github.com/gxhen/receiverAgnosticRFFI){:target="_blank"}
1. Guanxiong Shen, **Junqing Zhang***, Alan Marshall, Mikko Valkama, and Joseph Cavallaro, “Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification,” _IEEE Transactions on Information Forensics and Security_, vol. 18, pp. 2355 - 2367, Apr. 2023. [IEEE](https://ieeexplore.ieee.org/document/10100932){:target="_blank"}, [arXiv link](https://arxiv.org/abs/2207.03001){:target="_blank"}
* [Dataset: LoRa RFFI with Different Spreading Factors](https://ieee-dataport.org/documents/lorarffidatasetdifferentspreadingfactors){:target="_blank"}
* [Code: LoRa RFFI with Different Spreading Factors](https://github.com/gxhen/lengthVersatileRFFI){:target="_blank"}
1. Guanxiong Shen, **Junqing Zhang***, Alan Marshall, and Joseph Cavallaro, “Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa,” _IEEE Transactions on Information Forensics and Security_, vol. 17, pp. 774 - 787, Feb. 2022. [IEEE](https://ieeexplore.ieee.org/abstract/document/9715147){:target="_blank"}, [arXiv](https://arxiv.org/abs/2107.02867){:target="_blank"}
* [Dataset: LoRa RFFI](https://ieee-dataport.org/open-access/lorarffidataset){:target="_blank"}
* [Code: LoRa RFFI](https://github.com/gxhen/LoRa_RFFI){:target="_blank"}
Physical-Layer Authentication
1. Yijia Guo, **Junqing Zhang***, and Y.-W. Peter 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. [IEEE](https://ieeexplore.ieee.org/document/11141653){:target="_blank"}
* [Dataset: Wi-Fi Channel State Information Dataset for Mobile Physical Layer Authentication
](https://ieee-dataport.org/documents/wi-fi-channel-state-information-dataset-mobile-physical-layer-authentication){:target="_blank"}
* Source code: available on request
Wi-Fi Sensing
1. Guolin Yin, **Junqing Zhang***, Guanxiong Shen, and Yingying 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, Jan. 2024. [arXiv link](https://arxiv.org/abs/2203.02014){:target="_blank"},[IEEE](https://ieeexplore.ieee.org/document/9947336){:target="_blank"}
* Dataset: This study used public datasets; please consult the paper for details.
* [Code: FewSense paper](https://github.com/Guolin-Yin/FewSense){:target="_blank"}.