{"title":"A channel resilient RFF extraction scheme for cyclic prefix contained systems","authors":"Zhen Zhang , Aiqun Hu , Xinyu Qi , Tianshu Chen","doi":"10.1016/j.phycom.2024.102444","DOIUrl":null,"url":null,"abstract":"<div><p>Radio frequency fingerprint (RFF) based identification technique has been proved efficient for ensuring the validity of devices connected to network. However, it is still a tough task to extract robust RFF in the scenarios with multi-path channel and moving terminals. To solve this problem, this paper proposes a channel-resilient RFF extraction scheme which can effectively reduce the influences from complex channel condition and retain robust device fingerprint. In the proposed system, blind synchronization and symbol-scale carrier frequency offset (CFO) estimation are designed for signal preprocessing for preparations of the following RFF extraction. A cyclic-prefix based de-channel algorithm (CPDCA) which can effectively weaken channel interference is proposed to meet the channel robustness of our system. Additionally, symbol-scale feature stacking algorithm (SFSA) is applied for RFF denoising, which can further enhance the performance of proposed system. Experiments using practical dataset collected from Long Term Evolution (LTE)-V2X communication system has been carried out under different signal-to-noise ratio (SNR). The results demonstrate that the proposed scheme has the ability to extract channel-robust RFF and to achieve reliable classification performance under complex channel conditions.</p></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"66 ","pages":"Article 102444"},"PeriodicalIF":2.0000,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Communication","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1874490724001629","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Radio frequency fingerprint (RFF) based identification technique has been proved efficient for ensuring the validity of devices connected to network. However, it is still a tough task to extract robust RFF in the scenarios with multi-path channel and moving terminals. To solve this problem, this paper proposes a channel-resilient RFF extraction scheme which can effectively reduce the influences from complex channel condition and retain robust device fingerprint. In the proposed system, blind synchronization and symbol-scale carrier frequency offset (CFO) estimation are designed for signal preprocessing for preparations of the following RFF extraction. A cyclic-prefix based de-channel algorithm (CPDCA) which can effectively weaken channel interference is proposed to meet the channel robustness of our system. Additionally, symbol-scale feature stacking algorithm (SFSA) is applied for RFF denoising, which can further enhance the performance of proposed system. Experiments using practical dataset collected from Long Term Evolution (LTE)-V2X communication system has been carried out under different signal-to-noise ratio (SNR). The results demonstrate that the proposed scheme has the ability to extract channel-robust RFF and to achieve reliable classification performance under complex channel conditions.
期刊介绍:
PHYCOM: Physical Communication is an international and archival journal providing complete coverage of all topics of interest to those involved in all aspects of physical layer communications. Theoretical research contributions presenting new techniques, concepts or analyses, applied contributions reporting on experiences and experiments, and tutorials are published.
Topics of interest include but are not limited to:
Physical layer issues of Wireless Local Area Networks, WiMAX, Wireless Mesh Networks, Sensor and Ad Hoc Networks, PCS Systems; Radio access protocols and algorithms for the physical layer; Spread Spectrum Communications; Channel Modeling; Detection and Estimation; Modulation and Coding; Multiplexing and Carrier Techniques; Broadband Wireless Communications; Wireless Personal Communications; Multi-user Detection; Signal Separation and Interference rejection: Multimedia Communications over Wireless; DSP Applications to Wireless Systems; Experimental and Prototype Results; Multiple Access Techniques; Space-time Processing; Synchronization Techniques; Error Control Techniques; Cryptography; Software Radios; Tracking; Resource Allocation and Inference Management; Multi-rate and Multi-carrier Communications; Cross layer Design and Optimization; Propagation and Channel Characterization; OFDM Systems; MIMO Systems; Ultra-Wideband Communications; Cognitive Radio System Architectures; Platforms and Hardware Implementations for the Support of Cognitive, Radio Systems; Cognitive Radio Resource Management and Dynamic Spectrum Sharing.