Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa
Date: 11-June-2025
Time: 9:30 AM ET
Duration: Approximately 1 hour
About this topic:
Radio frequency fingerprint identification (RFFI) is a promising device authentication technique based on transmitter hardware impairments. The device-specific hardware features can be extracted at the receiver by analyzing the received signal and used for authentication. In this talk, the presenters we will present a scalable and channel-robust RFFI framework achieved by deep learning powered radio frequency fingerprint (RFF) extractor and channel independent features. Specifically, they leverage deep metric learning to train an RFF extractor, which has excellent generalization ability and can extract RFFs from previously unseen devices. Any devices can be enrolled via the pre-trained RFF extractor and the RFF database can be maintained efficiently for allowing devices to join and leave. Wireless channel impacts the RFF extraction and is tackled by exploiting channel independent features and data augmentation. They carried out extensive experimental evaluation involving 60 commercial off-the-shelf LoRa devices and a USRP N210 software defined radio platform. The results have successfully demonstrated that their framework can achieve excellent generalization abilities for rogue device detection and device classification as well as effective channel mitigation. They will also present their recent results mapping the inference algorithm to architectures and the FPGA implementation.
About the presenters:
Junqing Zhang (M’16-SM’25) received the B.Eng. and M.Eng. degrees in electrical engineering from Tianjin University, China in 2009 and 2012, respectively, and the Ph.D. degree in electronics and electrical engineering from Queen's University Belfast, UK in 2016.
He currently is a Senior Lecturer (Associate Professor) at the University of Liverpool since Oct. 2022. From Feb. 2016 to Jan. 2018, he was a Postdoctoral Research Fellow at Queen's University Belfast. From Feb. 2018 to Oct. 2022, he was a Tenure Track Fellow and then a Lecturer (Assistant Professor) at the University of Liverpool, UK. His research interests include the Internet of Things, wireless security, physical layer security, key generation, radio frequency fingerprint identification, and wireless sensing.
Dr. Zhang was a co-recipient of the IEEE WCNC 2025 Best Workshop Paper Award. He is a Senior Area Editor of IEEE Transactions on Information Forensics and Security and an Associate Editor of IEEE Transactions on Mobile Computing.
Guanxiong Shen (M’23) received the B.S. degree in telecommunications engineering from Xidian University, Xi’an, China, in 2019 and the Ph.D. degree in electrical and electronics engineering from the University of Liverpool, Liverpool, U.K., in 2023.
He is an Associate Professor Southeast University, Nanjing, China since 2023. His current research focuses on wireless physical layer security and the intersection of artificial intelligence and wireless systems.
Joseph R. Cavallaro (S'78-M'82-SM’05-F’15-LF’25) received the B.S. degree from the University of Pennsylvania, Philadelphia, Pa, in 1981, the M.S. degree from Princeton University, Princeton, NJ, in 1982, and the Ph.D. degree from Cornell University, Ithaca, NY, in 1988, all in electrical engineering.
He is currently a professor of electrical and computer engineering at Rice University, Houston, TX since 1988. From 1981 to 1983, he was with AT&T Bell Laboratories, Holmdel, NJ. During the 1996–1997 academic year, he served at the US National Science Foundation as Director of the Prototyping Tools and Methodology Program. He was a Nokia Foundation Fellow and a Visiting Professor at the University of Oulu, Finland in 2005. His research interests include computer arithmetic, and DSP, GPU, FPGA, and VLSI architectures for applications in wireless communications.
Dr. Cavallaro is a member of the IEEE SPS TC on Applied Signal Processing Systems. At the related IEEE SiPS workshop, he was TPC Co-Chair in 2016 and General Co-Chair in 2020, 2021, and 2024. He is a Past-Chair of the IEEE CASS TC on Circuits and Systems for Communications. He is a Senior Area Editor for the IEEE Transactions on Signal Processing and has served as an Associate Editor of the IEEE Transactions on Signal Processing and the IEEE Signal Processing Letters.
