[1]王 丹,赵 凯.基于距离预测分组的ALOHA算法[J].南京理工大学学报(自然科学版),2018,42(01):102.[doi:10.14177/j.cnki.32-1397n.2018.42.01.015]
 Wang Dan,Zhao Kai.ALOHA algorithm based on distance prediction grouping[J].Journal of Nanjing University of Science and Technology,2018,42(01):102.[doi:10.14177/j.cnki.32-1397n.2018.42.01.015]
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基于距离预测分组的ALOHA算法()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
42卷
期数:
2018年01期
页码:
102
栏目:
出版日期:
2018-02-28

文章信息/Info

Title:
ALOHA algorithm based on distance prediction grouping
文章编号:
1005-9830(2018)01-0102-05
作者:
王 丹1赵 凯2
1.郑州航空工业管理学院 电子通信工程学院,河南 郑州 450000; 2.铁道警察学院 公安技术系,河南 郑州 450000
Author(s):
Wang Dan1Zhao Kai2
1.School of Electronics and Communication Engineering,Zhengzhou University of Aeronautics,Zhengzhou 450000,China; 2.Department of Police Technology,Railway Police College,Zhengzhou 450000,China
关键词:
距离预测分组 物联网 射频识别 防碰撞算法 系统吞吐量 ALOHA算法
Keywords:
distance prediction grouping internet of things radio frequency identification anti-collision algorithm system throughput ALOHA algorithm
分类号:
TN911
DOI:
10.14177/j.cnki.32-1397n.2018.42.01.015
摘要:
针对传统ALOHA算法存在的吞吐量小、传输时延大等不足,提出了基于距离预测分组的ALOHA算法。该算法根据传输功率估计标签和阅读器之间距离,并根据距离估计结果将标签划为多个组,然后采用ALOHA算法对组内的标签进行相应的识别,减少标签碰撞概率,最后在MATLAB平台上进行了仿真实验。结果表明,相对于其它防碰撞算法,该文算法大幅度提升了系统的吞吐量,有效减少了平均传输时延,具有良好的实际应用价值。
Abstract:
Aiming at the shortcomings of traditional ALOHA algorithm,such as low throughput and large transmission delay,this paper presents an ALOHA algorithm based on distance prediction grouping.Firstly,the distance between tag and reader is estimated according to tag transmission power,and the tags are divided into several groups according to the estimation results; secondly,ALOHA algorithm is used to identify the tags to reduce the collision probability; finally,the simulation experiment is carried out on MATLAB platform.Results show that,compared with other anti-collision algorithms,the proposed algorithm has greatly improved system throughput,and it can effectively reduce average transmission delay,having good practical value.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-04-10 修回日期:2017-08-05 基金项目:河南省教育厅重点科研项目(16A510035) 作者简介:王丹(1981-),女,讲师,主要研究方向:信号及信息处理,E-mail:wangdan612@163.com; 通讯作者:赵凯(1982-),男,硕士,高级工程师,主要研究方向:计算机网络,E-mail:zhaokai966@163.com。 引文格式:王丹,赵凯. 基于距离预测分组的ALOHA算法[J]. 南京理工大学学报,2018,42(1):102-106. 投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2018-02-28