Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements

IMR OpenIR

	Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements
其他题名	Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements
	Wang Kai 1; Liu Yulin 2; Wan Qun 3; Jing Xiaojun 4
	2015
发表期刊	CHINESE JOURNAL OF ELECTRONICS
ISSN	1022-4653
卷号	24 期号:2 页码:388-392
摘要	In Wireless sensor networks (WSNs), missed measurements may be caused by the sensor malfunction and interruption of communication between sensor nodes. The feasibility of exact recovery of WSNs data with missed measurements is analyzed in the framework of compressed sensing. A new incomplete measurement model was developed and the data reconstruction algorithm was proposed. The required number of the missing measurements and the sparsity condition of network data are found for exact compressed sensing of WSNs data. Theoretical derivation shows that a WSNs data of length N with no more than M/(log(N/M)+1) nonzero coefficients can be exactly recovered with M Gaussian measurements, provided that fraction of the missed measurements is less than a quarter of the Restricted isometry property (RIP) constant squared. Simulation results validate the theoretical results.
其他摘要	In Wireless sensor networks (WSNs), missed measurements may be caused by the sensor malfunction and interruption of communication between sensor nodes. The feasibility of exact recovery of WSNs data with missed measurements is analyzed in the framework of compressed sensing. A new incomplete measurement model was developed and the data reconstruction algorithm was proposed. The required number of the missing measurements and the sparsity condition of network data are found for exact compressed sensing ofWSNs data. Theoretical derivation shows that aWSNs data of length N with no more than M/(log(N/M)+1) nonzero coefficients can be exactly recovered with M Gaussian measurements, provided that fraction of the missed measurements is less than a quarter of the Restricted isometry property (RIP) constant squared. Simulation results validate the theoretical results.
关键词	Wireless sensor networks Compressed sensing Missed measurements Data reconstruction
收录类别	CSCD
语种	英语
资助项目	[Program for New Century Excellent Talents in University] ; [Program for Innovative Research Team in University of Chongqing] ; [Key Project of Chongqing Natural Science Foundation] ; [Program for Fundamental and Advanced Research of Chongqing]
CSCD记录号	CSCD:5555360
引用统计	被引频次：3[CSCD] [CSCD记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/154723
专题	中国科学院金属研究所
作者单位	1.Chongqing Commun Institute, Chongqing 400035, Peoples R China 2.中国科学院金属研究所 3.University Elect Sci & Technol China, Chengdu 610054, Peoples R China 4.Beijing University Posts & Telecommun, Beijing 100876, Peoples R China
推荐引用方式 GB/T 7714	Wang Kai,Liu Yulin,Wan Qun,et al. Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements[J]. CHINESE JOURNAL OF ELECTRONICS,2015,24(2):388-392.
APA	Wang Kai,Liu Yulin,Wan Qun,&Jing Xiaojun.(2015).Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements.CHINESE JOURNAL OF ELECTRONICS,24(2),388-392.
MLA	Wang Kai,et al."Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements".CHINESE JOURNAL OF ELECTRONICS 24.2(2015):388-392.