基于树深度分组的RFID标签基数估计算法  

Cardinality Estimation of RFID Tags Based on Tree Depth Grouping

作　　者：郑遥 王晓梅[1] 杨东煜[1] 丁思淼 ZHENG Yao;WANG Xiaomei;YANG Dongyu;DING Simiao(Information Engineering University,Zhengzhou 450001,China)

机构地区：[1]信息工程大学

出　　处：《信息工程大学学报》2019年第3期275-279,共5页Journal of Information Engineering University

摘　　要：RFID技术已被广泛应用于各个领域,而阅读器范围内的标签基数估计问题一直是目前的研究重点。基于二项分布的标签估计算法不适合大规模的RFID环境,而已有的几何分布算法需要标签进行多次响应,增大有源标签能耗。提出一种基于树分组的RFID标签估计算法,提高标签估计的效率并降低标签估计的能耗。通过实验仿真,该算法在能量消耗和时间性能方面优于改进前的算法。RFID technology has been widely used in various fields,and tag cardinal number estimation within the scope of reader has been the focus of the current research.The binomial distribution-based tag estimation protocol is not suitable for large-scale RFID environment,and the existing geometric distribution protocol needs the tag to respond many times,which increases the energy consumption of the active tag.Therefore,in this paper,we propose a protocol for RFID tag estimation based on binary tree grouping,which can improve the efficiency and reduce the energy consumption of tag estimation.Simulation results show that the energy consumption and time cost of our protocol are better than the LOF protocol.

关 键 词：射频标签 ALOHA算法 标签基数估计 二项分布 

分 类 号：TN929[电子电信—通信与信息系统]