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Joint sparse observation and coding design for multiple phenomena monitoring
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Han, Chengcheng, Chen, Li, Zhao, Nan, Chen, Yunfei and Yu, F. Richard (2021) Joint sparse observation and coding design for multiple phenomena monitoring. IEEE Transactions on Communications, 69 (10). pp. 6987-7002. doi:10.1109/TCOMM.2021.3093331
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WRAP-joint-sparse-observation-coding-design-multiple-phenomena-monitoring-Chen-2021.pdf - Accepted Version - Requires a PDF viewer. Download (2379Kb) | Preview |
Official URL: http://dx.doi.org/10.1109/TCOMM.2021.3093331
Abstract
Energy-efficient designs play an important role in the Internet of Things (IoT) that monitors multiple phenomena, due to the limited power supply and complicated observation. In this paper, taking into account the power consumptions of observation, coding, and communication, we propose a joint sparse observation and coding scheme for energy-efficient monitoring of multiple phenomena using IoT. Through the analysis of outage performance, we find that the sparse observation and coding scheme can achieve the performance of the full observation scheme in which all nodes observe all phenomena with lower power consumption due to the dynamic and selective observation and coding. With the derived achievable rates and network power consumption, we study the trade-off between achievable rates and network power consumption that is determined by both the observation matrix and the coding matrix. For given rate constraints, we propose an optimization problem to minimize the network power consumption by jointly designing the observation and coding matrices. To solve this NP-hard problem efficiently, we propose a low-complexity algorithm with the convex-concave procedure. Moreover, to improve performance in high noise environment, we adopt collaboration among nodes to suppress observation noises and equalize bad observations by utilizing observation diversity. Finally, simulation results illustrate the superior performance of the proposed schemes.
| Item Type: | Journal Article | ||||||||||||
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| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||||||
| Library of Congress Subject Headings (LCSH): | Internet of things, Energy conservation, Digital communications, Coding theory, Sparse matrices -- Data processing | ||||||||||||
| Journal or Publication Title: | IEEE Transactions on Communications | ||||||||||||
| Publisher: | IEEE | ||||||||||||
| ISSN: | 0090-6778 | ||||||||||||
| Official Date: | October 2021 | ||||||||||||
| Dates: |
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| Volume: | 69 | ||||||||||||
| Number: | 10 | ||||||||||||
| Page Range: | pp. 6987-7002 | ||||||||||||
| DOI: | 10.1109/TCOMM.2021.3093331 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Reuse Statement (publisher, data, author rights): | © 2021 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. | ||||||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
| RIOXX Funder/Project Grant: |
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