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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
[ "王棋萍(1990-),女,湖南湘乡人,解放军理工大学硕士生,主要研究方向为无线网络安全。" ]
[ "魏祥麟(1985-),男,安徽砀山人,南京电讯技术研究所工程师,主要研究方向为数据中心网络、无线网络安全和网络异常检测。" ]
[ "范建华(1971-),男,安徽歙县人,南京电讯技术研究所研究员,主要研究方向为无线网络安全和认知无线电网络。" ]
[ "王统祥(1990-),男,山东临沂人,解放军理工大学博士生,主要研究方向为无线网络安全。" ]
[ "胡飞(1987-),男,江苏淮安人,解放军理工大学硕士生,主要研究方向为无线网络安全。" ]
网络出版日期:2016-12,
纸质出版日期:2016-12-25
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王棋萍, 魏祥麟, 范建华, 等. 面向多跳无线网络的多干扰源定位算法[J]. 通信学报, 2016,37(12):176-186.
Qi-ping WANG, Xiang-lin WEI, Jian-hua FAN, et al. Multi-hop wireless network oriented multiple jammers localization algorithm[J]. Journal on communications, 2016, 37(12): 176-186.
王棋萍, 魏祥麟, 范建华, 等. 面向多跳无线网络的多干扰源定位算法[J]. 通信学报, 2016,37(12):176-186. DOI: 10.11959/j.issn.1000-436x.2016284.
Qi-ping WANG, Xiang-lin WEI, Jian-hua FAN, et al. Multi-hop wireless network oriented multiple jammers localization algorithm[J]. Journal on communications, 2016, 37(12): 176-186. DOI: 10.11959/j.issn.1000-436x.2016284.
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。
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.
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