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尚弘.一种基于搜索树的轻量级RFID标签防碰撞方案[J].重庆邮电大学学报(自然科学版),2018,30(6):789-796. 本文二维码信息
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一种基于搜索树的轻量级RFID标签防碰撞方案
A lightweight RFID tags anti-collision scheme based on searching tree
投稿时间:2018-08-06  修订日期:2018-11-17
DOI: 10.3979/j.issn.1673-825X.2018.06.009
中文关键词:  射频识别(RFID)  防碰撞  搜索树  轻量级
English Keywords:radio frequency identification (RFID)  anti-collision  searching tree  lightweight
基金项目:
作者单位E-mail
尚弘 无锡太湖学院 物联网技术江苏省重点实验室,江苏 无锡 214064 75643982@qq.com 
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中文摘要:
      针对现有的RFID(radio frequency identification)搜索树防冲突方案由于查询命令过长,会产生大量的冗余数据,增加通信开销的问题,提出一种基于搜索树的轻量级防冲突方案。该方案设计了一种新颖的查询-响应模式(即单查询双响应),该方法能够使冲突标签分别根据2个后续时隙中的最大有效冲突位对下一个查询作出响应,将查询总数减少一半;该方案用计数器代替了标签中的前缀匹配电路,可消除前缀作为查询命令的参考参数。此外,该方案提出了一种预测识别方法以减少所需时隙总数。最后,该方案还提出了一种避免识别标签与未识别标签冲突的锁定技术,提高了标签的识别效率。实验结果表明,采用双应答模式和计数器触发的单次查询方式,通信开销总体上降低了42%;采用预测识别方式,吞吐量随着标签数量的增加而提高。
English Summary:
      The existing RFID (radio frequency identification) searching tree anti-collision schemes incur large amounts of redundancy data due to an excess of long query commands, which increases the communication overhead. The paper proposed a lightweight anti-collision scheme based on searching tree. At first, the scheme designed a novel query response mode (i.e., single query with duo responses), which can make the collided tags respond to the next query in two subsequent slots respectively according to their most significant collided bit, and reduce the total number of queries by half. The scheme replaced the prefix matching circuit in tag with a counter, which can eliminate the prefix as the reference parameter of query command. Besides, the scheme put forward a predictive identification method to decrease the total number of the required slots. Finally, the scheme also proposed a locking technique to avoid the identified tags colliding with the unidentified tags, which can improve the identification efficiency of tags. The experimental results show that the communication overhead is decreased overall 42% by using single query with duo responses mode and counter trigger, and that the throughput is improving with the number of tags by using predictive identification.
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