User Pairing and Power Allocation in Untrusted Multiuser NOMA for Internet of Things

Yuan, C; Ni, W; Zhang, K; Bai, J; Shen, J; Jamalipour, A

User Pairing and Power Allocation in Untrusted Multiuser NOMA for Internet of Things

Yuan, C Ni, W

Zhang, K Bai, J Shen, J Jamalipour, A

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Internet of Things Journal, 2023, 10, (15), pp. 13155-13167
Issue Date:: 2023-08-01

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Field	Value	Language
dc.contributor.author	Yuan, C
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.contributor.author	Zhang, K
dc.contributor.author	Bai, J
dc.contributor.author	Shen, J
dc.contributor.author	Jamalipour, A
dc.date.accessioned	2024-04-17T03:06:51Z
dc.date.available	2024-04-17T03:06:51Z
dc.date.issued	2023-08-01
dc.identifier.citation	IEEE Internet of Things Journal, 2023, 10, (15), pp. 13155-13167
dc.identifier.issn	2327-4662
dc.identifier.issn	2327-4662
dc.identifier.uri	http://hdl.handle.net/10453/178004
dc.description.abstract	In the Internet of Things (IoT), massive sensitive and confidential information is transmitted wirelessly, making security a serious concern. This is particularly true when technologies, such as nonorthogonal multiple access (NOMA), are used, making it possible for users to access each other's data. This article studies secure communications in multiuser NOMA downlink systems, where each user is potentially an eavesdropper. Resource allocation is formulated to achieve the maximum sum secrecy rate, meanwhile satisfying the users' data requirements and power constraint. We solve this nontrivial, mixed-integer nonlinear programming problem by decomposing it into power allocation with a closed-form solution, and user pairing obtained effectively using linear programming relaxation and barrier algorithm. These subproblems are solved iteratively until convergence, with the convergence rate rigorously analyzed. Simulations demonstrate that our approach outperforms its existing alternatives significantly in the sum secrecy rate and computational complexity.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Internet of Things Journal
dc.relation.isbasedon	10.1109/JIOT.2023.3262512
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 1005 Communications Technologies
dc.subject.classification	40 Engineering
dc.subject.classification	46 Information and computing sciences
dc.title	User Pairing and Power Allocation in Untrusted Multiuser NOMA for Internet of Things
dc.type	Journal Article
utslib.citation.volume	10
utslib.for	0805 Distributed Computing
utslib.for	1005 Communications Technologies
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2024-04-17T03:06:49Z
pubs.issue	15
pubs.publication-status	Published
pubs.volume	10
utslib.citation.issue	15

Abstract:

In the Internet of Things (IoT), massive sensitive and confidential information is transmitted wirelessly, making security a serious concern. This is particularly true when technologies, such as nonorthogonal multiple access (NOMA), are used, making it possible for users to access each other's data. This article studies secure communications in multiuser NOMA downlink systems, where each user is potentially an eavesdropper. Resource allocation is formulated to achieve the maximum sum secrecy rate, meanwhile satisfying the users' data requirements and power constraint. We solve this nontrivial, mixed-integer nonlinear programming problem by decomposing it into power allocation with a closed-form solution, and user pairing obtained effectively using linear programming relaxation and barrier algorithm. These subproblems are solved iteratively until convergence, with the convergence rate rigorously analyzed. Simulations demonstrate that our approach outperforms its existing alternatives significantly in the sum secrecy rate and computational complexity.

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http://hdl.handle.net/10453/178004