Journal of Terahertz Science and Electronic Information Technology , Volume. 20, Issue 12, 1305(2022)

Convolutional Neural Network Radio Frequency fingerprint identification method for co-existence of cooperative signal and spoofing signal

ZHANG Yaqi*, YANG Chun, LIU Youjiang, YANG Dalong, and QIU Yongtao
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    References(4)

    [5] [5] BRIK V,BANERJEE S,GRUTESER M,et al. Wireless device identification with radiometric signatures[C]// Proceedings of the 14th ACM international conference on Mobile computing and networking. San Francisco,California,USA:ACM, 2008:116-127.

    [7] [7] DUDCZYK J,KAWALEC A. Specific emitter identification based on graphical representation of the distribution of radar signal parameters[J]. Bulletin of the Polish Academy of Sciences:Technical Sciences, 2015,63(2):391-396. doi:10.1515/bpasts-2015-0044.

    [8] [8] KULIN M,KAZAZ T,MOERMAN I,et al. End-to-end learning from spectrum data:a deep learning approach for wireless signal identification in spectrum monitoring applications[J]. IEEE Access, 2017(6):18484-18501. doi:10.1109/ACCESS.2018.2818794.

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    ZHANG Yaqi, YANG Chun, LIU Youjiang, YANG Dalong, QIU Yongtao. Convolutional Neural Network Radio Frequency fingerprint identification method for co-existence of cooperative signal and spoofing signal[J]. Journal of Terahertz Science and Electronic Information Technology , 2022, 20(12): 1305

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    Paper Information

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    Received: Oct. 1, 2021

    Accepted: --

    Published Online: Feb. 17, 2023

    The Author Email: Yaqi ZHANG (zhangyaqi19@gscaep.ac.cn)

    DOI:10.11805/tkyda2021356

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