[1]邵豪,王伦文.基于压缩感知的无线通信网拓扑推断方法[J].探测与控制学报,2020,42(02):92.[doi:.]
 SHAO Hao,WANG Lunwen.Topology Inference Method for Wireless Communication Networks Based on Compressed Sensing[J].,2020,42(02):92.[doi:.]
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基于压缩感知的无线通信网拓扑推断方法()
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《探测与控制学报》[ISSN:1008-1194/CN:61-1316/TJ]

卷:
42
期数:
2020年02
页码:
92
栏目:
出版日期:
2020-04-15

文章信息/Info

Title:
Topology Inference Method for Wireless Communication Networks Based on Compressed Sensing
文章编号:
1008-1194(2020)02-0092-07
作者:
邵豪 王伦文
国防科技大学电子对抗学院,安徽 合肥 230037
Author(s):
SHAO Hao WANG Lunwen
Electronic Countermeasure Institute, National University of Defense Technology, Hefei 230037, China
关键词:
拓扑推断信号侦察时间序列压缩感知向量重构
Keywords:
topology Inference signal reconnaissance time series compressed sensing vector reconstruction
分类号:
TP391
DOI:
.
文献标志码:
A
摘要:
针对无线通信非合作方难以使用传统拓扑发现方法获取网络拓扑的问题,提出基于压缩感知的无线通信网拓扑推断方法。该方法首先通过节点发出数据信号和确认信号的时间接续关系,获取时间窗口内网络节点状态;其次构造适用于无线通信网络的压缩感知模型框架,通过重构算法恢复节点链接向量;最后根据节点双向匹配原则法与筛选状态迭代法,筛选链路并提取相应时刻的节点状态,再次重构链接向量直至算法收敛。仿真实验表明,该算法能通过少量节点状态极化数据准确推断网络拓扑结构,具有较高时效性,且能够适应环境噪声干扰。
Abstract:
To solve the problem that a non-cooperative party could not obtain the topology information of wireless communication networks by traditional topology discovery algorithm, a method to infer network topology by wireless signals was put proposed. Firstly, the status of nodes was obtained by the time-sequence relationships between data signal and reply signal. Secondly, a sparse vector recovery model was proposed, which was suitable for communication network by limited state sequences of nodes, and the link vectors were reconstructed. Finally, the correct states of links was extracted and the link vectors were reconstructed according to the bidirectional matching until the algorithm converged. The experiment results showed that the proposed algorithm could correctly infer the network topology with finite time series of the nodes. In addition, the algorithm had high timeliness and was less affected by the noise from environment.

参考文献/References:

[1]Wang C, Ning H, Bai Y, et al. A method of network topology optimization design considering application process characteristic[J]. Modern Physics Letters B, 2018, 32(7):1850091.
[2]Diamant R, Francescon R, Zorzi M. Topology-efficient discovery: a topology discovery algorithm for underwater acoustic networks[J]. IEEE Journal of Oceanic Engineering, 2017, PP(99):1-15.
[3]杨红娃, 潘高峰, 王巍. 战场干线网拓扑推断技术[J]. 通信对抗, 2009(3):14-17.
[4]Cavraro G, Arghandeh R. Power distribution network topology detection with time-series signature verification method[J]. IEEE Transactions on Power Systems, 2018, 33(4):3500-3509.
[5]Lee K, Wu Y, Bresler Y. Near optimal compressed sensing of sparse rank-one matrices via sparse power factorization[J]. IEEE Transactions on Information Theory, 2018, 64(3):1666-1698.
[6]Han X, Shen Z, Wang W X, et al. Robust reconstruction of complex networks from sparse data[J]. Physical Review Letters, 2015, 114(2):028701.
[7]Parsegov S E,Proskurnikov A V, Tempo R, et al. A novel multidimensional model of opinion dynamics in social networks[J]. Mathematics, 2015, 62(5):2270-2285.
[8]Shen Z, Wang W X, Fan Y, et al. Reconstructing propagation networks with natural diversity and identifying hidden sources[J]. Nature communications, 2014, 5(4): 23-29.
[9]Li L, Xu D, Peng H, et al. Reconstruction of complex network based on the noise via QR decomposition and compressed sensing[J]. Scientific reports, 2017, 7(1): 15-26.
[10]Su R Q, Lai Y C, Wang X, et al. Uncovering hidden nodes in complex networks in the presence of noise[J]. Scientific reports, 2014, 4(1): 39-44.
[11]王鹏,李红艳,张焘.基于时间聚合图的DTN网络最短时延路由算法[J].通信学报,2017, 38(1):1-8.
[12]魏松杰,孙鑫,赵茹东.SDN中IP欺骗数据分组网络溯源方法研究[J].通信学报,2018, 39(11):185-193.
[13]耿鹏, 柳艳. 基于复杂网络理论的无线传感器网络的连通性[J]. 探测与控制学报, 2016, 38(5):123-127.
[14]王红亮, 王帅, 刘文怡. 压缩感知实现方法及应用综述[J]. 探测与控制学报, 2014, 36(4):53-61.
[15]王红亮, 卢振国, 王帅,等. 基于稀疏度自适应算法的压缩感知[J]. 探测与控制学报, 2017, 39(5):43-47.
[16]Menezes M B C, Kim S, Huang R. Constructing a Watts-Strogatz network from a small-world network with symmetric degree distribution[J]. Plos One, 2017, 12(6):e0179120.
[17]Bobrowski O, Kahle M. Topology of random geometric complexes: a survey[J]. Journal of Applied & Computational Topology, 2018, 1(3):331-364.
[18]Campbell C, Aucott S, Ruths J, et al. Correlations in the degeneracy of structurally controllable topologies for networks[J]. Scientific Reports, 2017, 7:46251.

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备注/Memo

备注/Memo:
收稿日期:2019-12-20
基金项目:国防科技创新特区项目资助(17-H863-01-ZT-003-204-03);国家自然科学基金项目资助(61273302)
作者简介:邵豪(1995—),男,浙江金华人,硕士研究生,研究方向:网络行为分析、智能信息处理等。E-mail:shaohao64@outlook.com
更新日期/Last Update: 2020-05-15