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基于锁定位的射频识别自适应并行响应冲突树算法

RFID Adaptive Parallel Response Collision Tree Algorithm Based on Lock-Bit.

作者信息

Luo Xuan, Jia Xiaolin, Gu Yajun

机构信息

School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China.

Mobile Internet of Things and Radio Frequency Identification Technology Key Laboratory of Mianyang (MIOT&RFID), Mianyang 621010, China.

出版信息

Sensors (Basel). 2024 Jan 9;24(2):389. doi: 10.3390/s24020389.

Abstract

This paper proposes the Lock-Position-Based RFID Adaptive Parallel Collision Tree (LAPCT) algorithm to address the issues of excessive time slots required in the identification process of collision tree algorithms for multiple tags and the high communication complexity between the reader and multiple tags. The LAPCT algorithm adopts a single-query multiple-response mechanism and dynamically divides the response sub-cycle numbers in the identification cycle based on an adaptive strategy. It uses Manchester encoding to lock collision positions and generate a common query prefix, effectively reducing the number of reader queries. This reduction in queries decreases the total number of required time slots and transmitted bits during the reader-tag communication process, thereby improving the efficiency of multiple tag recognition. Theoretical and simulation experiments demonstrate that compared to similar algorithms, the LAPCT algorithm achieves a maximum reduction of 37% in total time slots required, a maximum improvement of 30% in recognition efficiency, and a maximum reduction of 90% in communication complexity. Furthermore, with an increase in the number of tags, the performance advantages of the LAPCT algorithm become more pronounced, making it suitable for large-scale tag scenarios.

摘要

本文提出了基于锁定位的射频识别自适应并行冲突树(LAPCT)算法,以解决多标签冲突树算法识别过程中所需时隙过多以及读写器与多个标签之间通信复杂度高的问题。LAPCT算法采用单查询多响应机制,并基于自适应策略在识别周期中动态划分响应子周期数。它使用曼彻斯特编码来锁定冲突位置并生成公共查询前缀,有效减少了读写器查询次数。查询次数的减少降低了读写器与标签通信过程中所需的总时隙数和传输位数,从而提高了多标签识别效率。理论和仿真实验表明,与类似算法相比,LAPCT算法所需的总时隙数最多可减少37%,识别效率最多可提高30%,通信复杂度最多可降低90%。此外,随着标签数量的增加,LAPCT算法的性能优势更加明显,使其适用于大规模标签场景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb7/10818424/1bde31d64fb5/sensors-24-00389-g001.jpg

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