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dc.contributor.authorZhang, Y.
dc.contributor.authorXiang, Y.
dc.contributor.authorZhang, L.
dc.contributor.authorRong, Yue
dc.contributor.authorGuo, S.
dc.date.accessioned2018-12-13T09:11:59Z
dc.date.available2018-12-13T09:11:59Z
dc.date.created2018-12-12T02:46:42Z
dc.date.issued2018
dc.identifier.citationZhang, Y. and Xiang, Y. and Zhang, L. and Rong, Y. and Guo, S. 2018. Secure Wireless Communications Based on Compressive Sensing: A Survey. IEEE Communications Surveys and Tutorials. 21 (2): pp. 1093-1111.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/71965
dc.identifier.doi10.1109/COMST.2018.2878943
dc.description.abstract

IEEE Compressive sensing (CS) has become a popular signal processing technique and has extensive applications in numerous fields such as wireless communications, image processing, magnetic resonance imaging, remote sensing imaging, and anology to information conversion, since it can realize simultaneous sampling and compression. In the information security field, secure CS has received much attention due to the fact that CS can be regarded as a cryptosystem to attain simultaneous sampling, compression and encryption when maintaining the secret measurement matrix. Considering that there are increasing works focusing on secure wireless communications based on CS in recent years, we produce a detailed review for the state-of-the-art in this paper. To be specific, the survey proceeds with two phases. The first phase reviews the security aspects of CS according to different types of random measurement matrices such as Gaussian matrix, circulant matrix, and other special random matrices, which establishes theoretical foundations for applications in secure wireless communications. The second phase reviews the applications of secure CS depending on communication scenarios such as wireless wiretap channel, wireless sensor network, internet of things, crowdsensing, smart grid, and wireless body area networks. Finally, some concluding remarks are given.

dc.titleSecure Wireless Communications Based on Compressive Sensing: A Survey
dc.typeJournal Article
dcterms.source.issn1553-877X
dcterms.source.titleIEEE Communications Surveys and Tutorials
curtin.note

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Science (EECMS)
curtin.accessStatusOpen access


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