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A partitioning approach to RFID identification

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posted on 2023-06-07, 07:23 authored by Jian Su, Alex X Liu, Zhengguo ShengZhengguo Sheng, Yongrui Chen
Radio-frequency identification (RFID) is a major enabler of Internet of Things (IoT), and has been widely applied in tag-intensive environments. Tag collision arbitration is considered as a crucial issue of such RFID system. To enhance the reading performance of RFID, numerous anti-collision algorithms have been presented in previous literatures. However, most of them suffer from the slot efficiency bottleneck of 0.368. In this paper, we revisit the performance of tag identification in Aloha-based RFID anti-collision approaches from the perspective of time efficiency. Based on comprehensive reviews and analysis of the existing algorithms, a novel partitioning approach is proposed to maximize identification performance in framed slotted Aloha based UHF RFID systems. In the proposed approach, the tag set is divided into many groups which only contains a few tags, and then each group is identified in sequence. Benefiting from the optimal partition, the proposed algorithm can achieve a significant performance improvement. Simulation results supplemented by prototyping tests show that the proposed solution achieves an asymptotical slot efficiency up to 0.4348, outperforming the existing UHF RFID solutions.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

IEEE/ACM Transactions on Networking

ISSN

1063-6692

Publisher

IEEE

Issue

5

Volume

28

Page range

2160-2173

Department affiliated with

  • Engineering and Design Publications

Notes

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2020-07-01

First Open Access (FOA) Date

2020-07-14

First Compliant Deposit (FCD) Date

2020-06-30

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