通信学报 ›› 2016, Vol. 37 ›› Issue (12): 176-186.doi: 10.11959/j.issn.1000-436x.2016284

• 学术通信 • 上一篇    

面向多跳无线网络的多干扰源定位算法

王棋萍1,魏祥麟2(),范建华2,王统祥1,胡飞1   

  1. 1 解放军理工大学通信工程学院,江苏 南京 210007
    2 南京电讯技术研究所,江苏 南京 210007
  • 出版日期:2016-12-25 发布日期:2017-05-15
  • 基金资助:
    国家重点基础研究发展计划(“973”计划)基金资助项目;国家自然科学基金资助项目;国家自然科学基金资助项目;江苏省自然科学基金资助项目;江苏省自然科学基金资助项目;江苏省自然科学基金资助项目

Multi-hop wireless network oriented multiple jammers localization algorithm

Qi-ping WANG1,Xiang-lin WEI2(),Jian-hua FAN2,Tong-xiang WANG1,Fei HU1   

  1. 1 College of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, China
    2 Nanjing Telecommunication Technology Research Institute, Nanjing 210007, China
  • Online:2016-12-25 Published:2017-05-15
  • Supported by:
    The National Key Basic Research and Development Program of China(973 Program);The National Natural Science Foundation of China;The National Natural Science Foundation of China;The Natural Science Foundation of Jiangsu Prov-ince;The Natural Science Foundation of Jiangsu Prov-ince;The Natural Science Foundation of Jiangsu Prov-ince

摘要:

提出一种面向多跳无线网络的多干扰源定位算法,主要包括3个步骤:基于梯度下降法的分组投递率谷点推定、基于梯度上升法的接收干扰强度(RJSS, received jamming signal strength)峰点推定和聚类分析。首先,算法从多个初始节点出发,采用梯度下降法,沿着分组投递率梯度下降最快的方向逼近干扰源,直至到达分组投递率谷点;然后应用功率自适应动态调整技术,采用梯度上升法,沿着接收干扰强度上升最快的方向继续逼近干扰源,直至接收干扰强度峰点(也称为RJSS停止节点);最后通过对无法与RJSS停止节点通信的邻居节点进行聚类分析,确定干扰源的数量和位置。模拟实验表明,与现有算法相比,所提算法可以有效降低多干扰源定位过程的定位误差;并且,当干扰源间距符合限定条件时,算法定位结果更优。

关键词: 多跳无线网络, 干扰攻击, 干扰源定位, 聚类

Abstract:

A multiple jammer localization algorithm in multi-hop wireless networks was proposed. The proposed algo-rithm contained three steps, packet delivery ratio (PDR) valley point determination based on gradient descent algorithm, received jamming signal strength (RJSS) peak point determination based on gradient ascent algorithm and cluster analysis. Firstly, the algorithm started from a few initial nodes and moved along the gradient descent direction of PDR to approach the jammers until reaches the PDR valley point. Then, the algorithm moved toward the jammers using power adaptation technique based on RJSS gradient ascent process until it reached the RJSS peak point. Finally, through applying cluster analysis on the neighbour nodes which fail to communicate with RJSS peak points, the number and positions of the jam-mers can be estimated. Experimental results have verified that the proposed algorithm can improve the accuracy of local-ization compared with existed localization algorithms. Furthermore, the performance of the proposed algorithm is promi-nent when the distance of jammers accords with constraint condition.

Key words: multi-hop wireless network, jamming attack, jammer localization, cluster

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