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A Physical Layer Algorithm for Estimation of Number of Tags in UHF RFID Anti-Collision Design

Zhong Huang1, Jian Su2, Guangjun Wen1, Wenxian Zheng3, Chu Chu1, Yijun Zhang4,*, Yibo Zhang5

School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Nanjing University of Information Science & Technology, Nanjing, 210044, China.
Shenzhen Intellifusion Technologies Co., Shenzhen, 518000, China.
School of Foreign Languages, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Department of Mechanical Engineering, University of British Columbia, Vancouver, Canada.

* Corresponding Author: Yijun Zhang. Email: email.

Computers, Materials & Continua 2019, 61(1), 399-408. https://doi.org/10.32604/cmc.2019.05876

Abstract

A priori knowledge of the number of tags is crucial for anti-collision protocols in slotted UHF RFID systems. The number of tags is used to decide optimal frame length in dynamic frame slotted ALOHA (DFSA) and to adjust access probability in random access protocols. Conventional researches estimate the number of tags in MAC layer based on statistics of empty slots, collided slots and successful slots. Usually, a collision detection algorithm is employed to determine types of time slots. Only three types are distinguished because of lack of ability to detect the number of tags in single time slot. In this paper, a physical layer algorithm is proposed to detect the number of tags in a collided slot. Mean shift algorithm is utilized, and some properties of backscatter signals are investigated. Simulation results verify the effectiveness of the proposed solution in terms of low estimation error with a high SNR range, outperforming the existing MAC layer approaches.

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Cite This Article

Z. Huang, J. Su, G. Wen, W. Zheng, C. Chu et al., "A physical layer algorithm for estimation of number of tags in uhf rfid anti-collision design," Computers, Materials & Continua, vol. 61, no.1, pp. 399–408, 2019.

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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