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Fusion-based cooperative support identification for compressive networked sensing

Fusion-based cooperative support identification for compressive networked sensing
Fusion-based cooperative support identification for compressive networked sensing
This paper proposes a fusion-based cooperative support identification scheme for distributed compressive sparse signal recovery via resource-constrained wireless sensor net- works. The proposed support identification protocol involves: (i) local sparse sensing for economizing data gathering and storage, (ii) local binary decision making for partial support knowledge inference, (iii) binary information exchange among active nodes, and (iv) binary data aggregation for support estimation. Then, with the aid of the estimated signal support, a refined local decision is made at each node. Only the measurements of those informative nodes will be sent to the fusion center, which employs a weighted l_1-minimization for global signal reconstruction. The design of a Bayesian local decision rule is discussed, and the average communication cost is analyzed. Computer simulations are used to illustrate the effectiveness of the proposed scheme.
2162-2337
157-161
Yang, Ming Hsun
0b43e64a-a7b1-4fd6-928b-7e307acf0cee
Wu, Jwo Yuh
1c95bdaf-16e4-4c34-85b7-2df0eb2a1c0e
Wang, Tsang Yi
7f1c0642-9107-4096-b255-799aff0b3176
Maunder, Robert
76099323-7d58-4732-a98f-22a662ccba6c
Gau, Rung-Hung
48242953-b2f5-47bd-8279-a888e912aa6c
Yang, Ming Hsun
0b43e64a-a7b1-4fd6-928b-7e307acf0cee
Wu, Jwo Yuh
1c95bdaf-16e4-4c34-85b7-2df0eb2a1c0e
Wang, Tsang Yi
7f1c0642-9107-4096-b255-799aff0b3176
Maunder, Robert
76099323-7d58-4732-a98f-22a662ccba6c
Gau, Rung-Hung
48242953-b2f5-47bd-8279-a888e912aa6c

Yang, Ming Hsun, Wu, Jwo Yuh, Wang, Tsang Yi, Maunder, Robert and Gau, Rung-Hung (2020) Fusion-based cooperative support identification for compressive networked sensing. IEEE Wireless Communications Letters, 9 (2), 157-161. (doi:10.1109/LWC.2019.2946552).

Record type: Article

Abstract

This paper proposes a fusion-based cooperative support identification scheme for distributed compressive sparse signal recovery via resource-constrained wireless sensor net- works. The proposed support identification protocol involves: (i) local sparse sensing for economizing data gathering and storage, (ii) local binary decision making for partial support knowledge inference, (iii) binary information exchange among active nodes, and (iv) binary data aggregation for support estimation. Then, with the aid of the estimated signal support, a refined local decision is made at each node. Only the measurements of those informative nodes will be sent to the fusion center, which employs a weighted l_1-minimization for global signal reconstruction. The design of a Bayesian local decision rule is discussed, and the average communication cost is analyzed. Computer simulations are used to illustrate the effectiveness of the proposed scheme.

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WCL2019-0085.R1_(Final_version) - Accepted Manuscript
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Accepted/In Press date: 7 October 2019
e-pub ahead of print date: 10 October 2019
Published date: February 2020
Additional Information: “© 2019 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.”

Identifiers

Local EPrints ID: 434869
URI: http://eprints.soton.ac.uk/id/eprint/434869
ISSN: 2162-2337
PURE UUID: 05d2c023-8f4d-44f4-8291-344d64c9a055
ORCID for Robert Maunder: ORCID iD orcid.org/0000-0002-7944-2615

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Date deposited: 14 Oct 2019 16:30
Last modified: 07 Oct 2020 01:55

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Contributors

Author: Ming Hsun Yang
Author: Jwo Yuh Wu
Author: Tsang Yi Wang
Author: Robert Maunder ORCID iD
Author: Rung-Hung Gau

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