NDLI: Localization of wireless sensors using compressive sensing for manifold learning

Content Provider	IEEE Xplore Digital Library
Author	Chen Feng Valaee, S. Zhenhui Tan
Copyright Year	2009
Description	Author affiliation: State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University (Zhenhui Tan) \|\| Department of Electrical and Computer Engineering, University of Toronto (Chen Feng; Valaee, S.)
Abstract	In this paper, a novel compressive sensing for manifold learning protocol (CSML) is proposed for localization in wireless sensor networks (WSNs). Intersensor communication costs are reduced significantly by applying the theory of compressive sensing, which indicates that sparse signals can be recovered from far fewer samples than that needed by the Nyquist sampling theorem. We represent the pair-wise distance measurement as a sparse matrix. Instead of sending full pair-wise measurement data to a central node, each sensor transmits only a small number of compressive measurements. And the full pair-wise distance matrix can be well reconstructed from these noisy compressive measurements in the central node, only through an ℓ-minimization algorithm. The proposed method reduces the overall communication bandwidth requirement per sensor such that it increases logarithmically with the number of sensors and linearly with the number of neighbors, while achieves high localization accuracy. CSML is especially suitable for manifold learning based localization algorithms. Simulation results demonstrate the performance of the proposed protocol on both the localization accuracy and the communication cost reduction.
Starting Page	2715
Ending Page	2719
File Size	304859
Page Count	5
File Format	PDF
ISBN	9781424451227
e-ISBN	9781424451234
DOI	10.1109/PIMRC.2009.5449918
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-13
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless sensor networks Costs Manifolds Laboratories Rails Traffic control Railway safety Sparse matrices Protocols Energy measurement Wireless Sensor Networks Compressive Sensing Manifold Learning CSML localization
Content Type	Text
Resource Type	Article

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