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Volume 7 Issue 6
Oct.  2020

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2020  >  7(6): 1593-1603
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
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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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    Abstract
  • 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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  • [1]
    X. Tan, H. Wang, L. Z. Fu, J. Y. Wang, H. Min, and D. W. Engels, “Collision detection and signal recovery for UHF RFID systems,” IEEE Transa. Autom. Science and Engineering, vol. 15, no. 1, pp. 239–250, 2016.
    [2]
    L. Zhang, W. Xiang, and X. Tang, “An adaptive anticollision protocol for large-scale rfid tag identification,” Wireless Comm. Letters IEEE, vol. 3, no. 6, pp. 601–604, 2014. doi: 10.1109/LWC.2014.2359461
    [3]
    H. F. Wu, Y. Zeng, J. H. Feng, and Y. Gu, “Binary tree slotted ALOHA for passive RFID tag anticollision,” IEEE Trans. Parallel and Distributed Systems, vol. 24, no. 1, pp. 19–31, 2013. doi: 10.1109/TPDS.2012.120
    [4]
    M. Shao, X. F. Jin, and L. B. Jin. An improved dynamic adaptive multi-tree search anti-collision algorithm based on RFID. in Proc. Int Conf. Data Science and Advanced Analytics, Shanghai, China: IEEE, pp. 72–75, 2015.
    [5]
    H. F. Wu and Y. Zeng, “Bayesian tag estimate and optimal frame length for anti-collision ALOHA RFID system,” IEEE Trans. Autom. Science and Engineering, vol. 7, no. 4, pp. 963–969, 2010.
    [6]
    M. Mayer and N. Goertz, “RFID tag acquisition via compressed sensing: Fixed vs. random signature assignment,” IEEE Trans. Wireless Communications, vol. 15, no. 3, pp. 2118–2129, 2016. doi: 10.1109/TWC.2015.2498922
    [7]
    J. S. Han, C. Qian, P. L. Yang, D. Ma, Z. P. Jiang, W. Xi, and J. Z. Zhao, “Geneprint: Generic and accurate physical-layer identification for UHF RFID tags,” IEEE/ACM Trans. Networking, vol. 24, no. 2, pp. 846–858, 2016. doi: 10.1109/TNET.2015.2391300
    [8]
    M. Benbaghdad, B. Fergani, and S. Tedjini, “Toward a new phy layer scheme for decoding tags collision signal in UHF RFID system,” IEEE Comm. Letters, vol. 20, no. 11, pp. 2233–2236, 2016. doi: 10.1109/LCOMM.2016.2601321
    [9]
    Y. Q. Zheng and M. Li, “P-mti: Physical-layer missing tag identification via compressive sensing,” IEEE/ACM Trans. Networking, vol. 23, no. 4, pp. 1356–1366, 2015. doi: 10.1109/TNET.2014.2326460
    [10]
    P. Ishwerya, V. N. Kumar, and G. Lakshminarayanan. An efficient digital baseband encoder for short range wireless communication applications. in Proc. Int. Conf. Electrical, Electronics, and Optimization Techniques, Chennai, India: IEEE, pp. 2775–2779, 2016.
    [11]
    F. Zhu, B. Xiao, J. Liu, and L. J. Chen, “Efficient physical-layer unknown tag identification in large-scale RFID systems,” IEEE Trans. Comm., vol. 65, no. 1, pp. 283–295, 2017.
    [12]
    X. Yang, H. F. Wu, Y. Zeng, and F. Gao, “Captureaware estimation for the number of RFID tags with lower complexity,” IEEE Comm. Letters, vol. 17, no. 10, pp. 1873–1876, 2013. doi: 10.1109/LCOMM.2013.082413.130765
    [13]
    J. Kaitovic and M. Rupp. RFID physical layer collision recovery receivers with spatial filtering. in Proc. IEEE Int. Conf. RFID Technology and Applications, IEEE, pp. 39–44, 2015.
    [14]
    M. Benbaghdad, B. Fergani, S. Tedjini, and E. Perret. Simulation and measurement of collision signal in passive UHF RFID system and edge transition anti-collision algorithm. in Proc. RFID Technology and Applications Conf., Tampere, Finland: IEEE, pp. 277–282, 2014.
    [15]
    F. Ricciato and P. Castiglione, “Pseudo-random aloha for enhanced collision-recovery in RFID,” IEEE Comm. Letters, vol. 17, no. 3, pp. 608–611, 2013. doi: 10.1109/LCOMM.2013.011513.122109
    [16]
    Y. X. Hou, J. J. Ou, Y. Q. Zheng, and M. Li, “Place: Physical layer cardinality estimation for largescale RFID systems,” IEEE/ACM Trans. Networking, vol. 24, no. 5, pp. 2702–2714, 2016. doi: 10.1109/TNET.2015.2481999
    [17]
    D. W. Shen, G. Woo, D. P. Reed, A. B. Lippman, and J. Y. Wang. Separation of multiple passive RFID signals using software defined radio. in Proc. IEEE Int. Conf. RFID, Orlando, FL, USA: IEEE, pp. 139–146, 2009.
    [18]
    K. Fyhn, R. M. Jacobsen, P. Popovski, A. Scaglione, and T. Larsen, “Multipacket reception of passive UHF RFID tags: A communication theoretic approach,” IEEE Trans. Signal Processing, vol. 59, no. 9, pp. 4225–4237, 2016.
    [19]
    C. Angerer, R. Langwieser, and M. Rupp, “RFID reader receivers for physical layer collision recovery,” IEEE Trans. Communications, vol. 58, no. 12, pp. 3526–3537, 2010. doi: 10.1109/TCOMM.2010.101910.100004
    [20]
    H. J. Duan, H. F. Wu, and Y. Zeng, “Channel estimation for recovery of UHF RFID tag collision on physical layer,” J. Electronics and Information Technology, pp. 1–5, 2016.
    [21]
    EPC radio frequency identity protocols class-1 generation-2 UHF RFID protocol for communications at 860 MHz−960 MHz. 2013.
    [22]
    M. Benbaghdad, B. Fergani, and S. Tedjini, “Backscatter signal model of passive UHF RFID tag. application to collision detection,” Electronics Letters, vol. 52, no. 11, pp. 974–976, 2016. doi: 10.1049/el.2015.3974
    [23]
    J. J. Ou, M. Li, and Y. Q. Zheng. Come and be served: Parallel decoding for COTS RFID tags. in Proc. Int. Conf. Mobile Computing and Networking, pp. 500–511, 2015.
    [24]
    P. Hu, P. Zhang, and D. Ganesan, “Laissez-faire: Fully asymmetric backscatter communication,” ACM SIGCOMM Computer Comm. Review, vol. 45, no. 4, pp. 255–267, 2015.
    [25]
    A. Bletsas, J. Kimionis, A. G. Dimitriou, and G. N. Karystinos, “Single-antenna coherent detection of collided fm0 RFID signals,” IEEE Trans. Comm., vol. 60, no. 3, pp. 756–766, 2012. doi: 10.1109/TCOMM.2011.020612.110212
    [26]
    S. O. Haykin. Neural Networks and Learning Machines. Pearson Schweiz Ag, 2009.
    [27]
    J. Z. Li, H. F. Wu, Y. Zeng, and Y. Shen. FM0 decode for collided RFID tag signals with frequency drift. in Proc. 2nd Int. Conf. Image, Vision and Computing, Chengdu, China: IEEE, pp. 941–945, 2017.
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    Highlights

    • 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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