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Volume 7 Issue 6
Oct.  2020

IEEE/CAA Journal of Automatica Sinica

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Junzhi Li, Haifeng Wu and Yu Zeng, "Recovery of Collided RFID Tags With Frequency Drift on Physical Layer," IEEE/CAA J. Autom. Sinica, vol. 7, no. 6, pp. 1593-1603, Nov. 2020. doi: 10.1109/JAS.2019.1911720
Citation: Junzhi Li, Haifeng Wu and Yu Zeng, "Recovery of Collided RFID Tags With Frequency Drift on Physical Layer," IEEE/CAA J. Autom. Sinica, vol. 7, no. 6, pp. 1593-1603, Nov. 2020. doi: 10.1109/JAS.2019.1911720

Recovery of Collided RFID Tags With Frequency Drift on Physical Layer

doi: 10.1109/JAS.2019.1911720
Funds:  This work was supported by the National Natural Science Foundation of China (61762093), the 17th Batches of Young and Middle-aged Leaders in Academic and Technical Reserved Talents Project of Yunnan Province (2014HB019), the Key Applied and Basic Research Foundation of Yunnan Province (2018FA036), and the Program for Innovative Research Team (in Science and Technology) in University of Yunnan Province
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  • In a passive ultra-high frequency (UHF) radio frequency identification (RFID) system, the recovery of collided tag signals on a physical layer can enhance identification efficiency. However, frequency drift is very common in UHF RFID systems, and will have an influence on the recovery on the physical layer. To address the problem of recovery with the frequency drift, this paper adopts a radial basis function (RBF) network to separate the collision signals, and decode the signals via FM0 to recovery collided RFID tags. Numerical results show that the method in this paper has better performance of symbol error rate (SER) and separation efficiency compared to conventional methods when frequency drift occurs.


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    • The influence of frequency drift on the separation of collision tag signals is considered.
    • An adaptive radial basis function (RBF) neural network is introduced to separate the collision tag signals in a UHF RFID system.
    • An FM0 decoding algorithm is proposed to decode separated tag signals by RBF.


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