Wireless Physical-Layer Identification: Modeling and Validation
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Abstract (arXiv)
The wireless physical-layer identification (WPLI) techniques utilize the unique features of the physical waveforms of wireless signals to identify and classify authorized devices. As the inherent physical layer features are difficult to forge, WPLI is deemed as a promising technique for wireless security solutions. However, as of today it still remains unclear whether existing WPLI techniques can be applied under real-world requirements and constraints. In this paper, through both theoretical modeling and experiment validation, the reliability and differentiability of WPLI techniques are rigorously evaluated, especially under the constraints of state-of-art wireless devices, real operation environments, as well as wireless protocols and regulations. Specifically, a theoretical model is first established to systematically describe the complete procedure of WPLI. More importantly, the proposed model is then implemented to thoroughly characterize various WPLI techniques that utilize the spectrum features coming from the non-linear RF-front-end, under the influences from different transmitters, receivers, and wireless channels. Subsequently, the limitations of existing WPLI techniques are revealed and evaluated in details using both the developed theoretical model and in-lab experiments. The real-world requirements and constraints are characterized along each step in WPLI, including i) the signal processing at the transmitter (device to be identified), ii) the various physical layer features that originate from circuits, antenna, and environments, iii) the signal propagation in various wireless channels, iv) the signal reception and processing at the receiver (the identifier), and v) the fingerprint extraction and classification at the receiver.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Oct 2015.
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Citing papers per year: 2021: 4; 2022: 2; 2023: 0; 2024: 1; 2025: 2; 2026: 1.
10 papers.
- 2022A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challengescited by 15
- 2021Machine Learning for the Detection and Identification of Internet of Things (IoT) Devices: A Surveycited by 9
- 2021A Generalizable Model-and-Data Driven Approach for Open-Set RFF Authenticationcited by 7
- 2022Disentangled Representation Learning for RF Fingerprint Extraction under Unknown Channel Statisticscited by 5
- 2021Open Set RF Fingerprinting using Generative Outlier Augmentationcited by 2
- 2025Noise-Robust Radio Frequency Fingerprint Identification Using Denoise Diffusion Modelcited by 2
- 2024AoA-Based Physical Layer Authentication in Analog Arrays under Impersonation Attackscited by 1
- 2025Exploiting Radio Frequency Fingerprints for Device Identification: Tackling Cross-receiver Challenges in the Source-data-free Scenariocited by 1
- 2021Real-time Wireless Transmitter Authorization: Adapting to Dynamic Authorized Sets with Information Retrievalcited by 0
- 2026Rapid LoRA Aggregation for Wireless Channel Adaptation in Open-Set Radio Frequency Fingerprintingcited by 0
- 2026Rapid LoRA Aggregation for Wireless Channel Adaptation in Open-Set Radio Frequency Fingerprinting14 Apr 2026
- 2025Exploiting Radio Frequency Fingerprints for Device Identification: Tackling Cross-receiver Challenges in the Source-data-free Scenario18 Dec 2025
- 2025Noise-Robust Radio Frequency Fingerprint Identification Using Denoise Diffusion Model7 Mar 2025
- 2024AoA-Based Physical Layer Authentication in Analog Arrays under Impersonation Attacks11 Jul 2024
- 2022Disentangled Representation Learning for RF Fingerprint Extraction under Unknown Channel Statistics4 Aug 2022
- 2022A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challenges3 Jan 2022
- 2021Real-time Wireless Transmitter Authorization: Adapting to Dynamic Authorized Sets with Information Retrieval4 Nov 2021
- 2021Open Set RF Fingerprinting using Generative Outlier Augmentation30 Aug 2021
- 2021A Generalizable Model-and-Data Driven Approach for Open-Set RFF Authentication10 Aug 2021
- 2021Machine Learning for the Detection and Identification of Internet of Things (IoT) Devices: A Survey25 Jan 2021