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计算机工程

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基于鲁棒估计的最大前缀RFID 防碰撞算法

王 勇 1a,1b ,唐小虎 1b ,张莉涓 1b ,杨瑞琴 2   

  1. (1. 西南交通大学a. 物理科学与技术学院; b. 信息科学与技术学院,成都610031; 2. 中国石油四川成都销售分公司,成都610072)
  • 收稿日期:2013-12-30 出版日期:2015-02-15 发布日期:2015-02-13
  • 作者简介:王 勇(1974 - ),男,讲师,主研方向:射频识别,嵌入式系统;唐小虎,教授、博士生导师;张莉涓,博士研究生;杨瑞琴,工 程师。
  • 基金资助:
    中央高校基本科研业务费专项基金资助项目(SWJTU09BR246);四川省科技创新苗子工程基金资助项目(2010-016)。

Maximized Prefix Anti-collision Algorithm for RFID Based on Robust Estimation

WANG Yong 1a,1b ,TANG Xiaohu 1b ,ZHANG Lijuan 1b ,YANG Ruiqin 2   

  1. (1a. School of Physical Science and Technology,1b. School of Information Science and Technology, Southwest Jiaotong University,Chengdu 610031,China; 2. Chengdu Sales Branch in Sichuan,China National Petroleum Corporation,Chengdu 610072,China)
  • Received:2013-12-30 Online:2015-02-15 Published:2015-02-13

摘要: 针对射频识别(RFID)系统中标签数量未知的情况,采用传统ALOHA 算法进行标签估计,在标签数量较大而初始帧长度较小造成估计误差较大时,初始帧长度为固定值,通过改变响应标签数量的方式,达到准确估计标签的目的。研究标签鲁棒估计算法和随机前缀查找树(PRQT)防碰撞算法,在此基础上提出基于鲁棒估计的自适应最大前缀查找树(PMQT)防碰撞算法。理论分析和仿真结果表明,该算法系统效率可达50% 以上。PMQT 算法 比PRQT 算系统效率提高18% ~30% ,对标签估计偏差具有较高的鲁棒性。

关键词: 射频识别, 标签识别, 标签估计, 防碰撞算法, 鲁棒性, 自适应

Abstract: In the research of Radio Frequency Identification (RFID) system,when the number of unknown tags is estimated by using the traditional ALOHA algorithm,the large number of tags and the smaller initial frame length will cause large error. Using the initial fixed length of the frame,reader changes the response method to achieve an accurate tag number estimation. This paper studies a robust tag estimation method and the Prefix Randomized Query Tree(PRQT) algorithm,and then proposes Prefix Maximized Query Tree(PMQT) tag anti-collision protocol. The theoretic analysis shows that the system efficiency is more than 50% . The simulation result demonstrates that PMQT outperforms PRQT by about 18% ~30% with respect to the system efficiency. In addition,PMQT algorithm has tolerance to the inaccuracy of tag estimation.

Key words: Radio Frequency Identification ( RFID ), tag identification, tag estimation, anti-collision algorithm, robustness;self-adaptive

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