Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/172931
Title: | Secure spectrum sharing for satellite internet-of-things based on blockchain | Authors: | Wang, Li Zheng, Yuhang Zhang, Yu Li, Feng |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2023 | Source: | Wang, L., Zheng, Y., Zhang, Y. & Li, F. (2023). Secure spectrum sharing for satellite internet-of-things based on blockchain. Wireless Personal Communications, 131(1), 357-369. https://dx.doi.org/10.1007/s11277-023-10433-0 | Journal: | Wireless Personal Communications | Abstract: | Satellite Internet-of-Things (IoT) is a critical part to build information infrastructure for environmental and ecological monitoring in remote areas where the cellular networks are uneasy to cover. When massive IoT terminals pour in the crowded satellite channels, how to enhance the spectrum utility of satellite band and guarantee the system capacity calls for full investigations. In this paper, a secure spectrum optimization scheme is proposed in satellite IoT by introducing blockchain to hamper malicious users to involve in the spectrum sharing. A market-oriented spectrum optimization strategy is designed to improve the satellite systems’ benefits wherein the heterogeneous satellite channels are fully be considered and priced. In this circumstance, differentiated pricing is adopted to satisfy the various spectrum users’ demands. When applying blockchain to secure the spectrum trading, the edge computing along with the mechanism of user reputation are devised to address the concerns of limited computation power for general IoT devices. Besides, the consensus algorithm of Delegated Proof of Stake is used to improve the computing efficiency so as to better fit in the application circumstance of satellite IoT. Numerical results are provided to evaluate the performances of our proposed solution on satellite channel pricing and system benefits. | URI: | https://hdl.handle.net/10356/172931 | ISSN: | 0929-6212 | DOI: | 10.1007/s11277-023-10433-0 | Schools: | School of Computer Science and Engineering | Rights: | © 2023 The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Journal Articles |
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