Joint Optimization of Beamforming and Noise Injection for Covert Downlink Transmissions in Cell-Free Internet of Things Networks

Xing, J; Lv, T; Li, W; Ni, W; Jamalipour, A

Joint Optimization of Beamforming and Noise Injection for Covert Downlink Transmissions in Cell-Free Internet of Things Networks

Xing, J Lv, T Li, W Ni, W

Jamalipour, A

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Internet of Things Journal, 2024, 11, (6), pp. 10525-10536
Issue Date:: 2024-03-15

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Field	Value	Language
dc.contributor.author	Xing, J
dc.contributor.author	Lv, T
dc.contributor.author	Li, W
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.contributor.author	Jamalipour, A
dc.date.accessioned	2024-08-07T04:36:56Z
dc.date.available	2024-08-07T04:36:56Z
dc.date.issued	2024-03-15
dc.identifier.citation	IEEE Internet of Things Journal, 2024, 11, (6), pp. 10525-10536
dc.identifier.issn	2327-4662
dc.identifier.issn	2327-4662
dc.identifier.uri	http://hdl.handle.net/10453/180210
dc.description.abstract	The development of Internet of Things (IoT) systems has given rise to security concerns stemming from the exposure of wireless channels and the exponential growth of connected devices. The security challenges can be severer in the next-generation IoT systems that can disperse over large areas under a cell-free (CF) network setting. In this article, we propose a novel covert downlink transmission scheme that jointly optimizes beamforming and artificial noise (AN) vectors to obscure critical transmissions at an eavesdropper in CF IoT Networks. We classify access points (APs) as information APs (IAPs) and noise APs (NAPs) based on their proximity to the IoT devices. IAPs transmit information while NAPs generate AN to prevent eavesdropping. We derive a closed-form solution for the detection error probability. By using the Lagrangian dual algorithm, the complex logarithmic problem is transformed into sum-of-ratios form. Then, we use semidefinite relaxation (SDR) to maximize the covert transmit rate. Numerical results show that the proposed scheme outperforms the state of the art, i.e., the suboptimal Rand- AP scheme, by increasing the transmission rate by more than 23% while maintaining covertness and is better than the rest of the benchmark schemes.
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.2023.3326275
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0805 Distributed Computing, 1005 Communications Technologies
dc.subject.classification	40 Engineering
dc.subject.classification	46 Information and computing sciences
dc.title	Joint Optimization of Beamforming and Noise Injection for Covert Downlink Transmissions in Cell-Free Internet of Things Networks
dc.type	Journal Article
utslib.citation.volume	11
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	recently_added	*
dc.date.updated	2024-08-07T04:36:55Z
pubs.issue	6
pubs.publication-status	Published
pubs.volume	11
utslib.citation.issue	6

Abstract:

The development of Internet of Things (IoT) systems has given rise to security concerns stemming from the exposure of wireless channels and the exponential growth of connected devices. The security challenges can be severer in the next-generation IoT systems that can disperse over large areas under a cell-free (CF) network setting. In this article, we propose a novel covert downlink transmission scheme that jointly optimizes beamforming and artificial noise (AN) vectors to obscure critical transmissions at an eavesdropper in CF IoT Networks. We classify access points (APs) as information APs (IAPs) and noise APs (NAPs) based on their proximity to the IoT devices. IAPs transmit information while NAPs generate AN to prevent eavesdropping. We derive a closed-form solution for the detection error probability. By using the Lagrangian dual algorithm, the complex logarithmic problem is transformed into sum-of-ratios form. Then, we use semidefinite relaxation (SDR) to maximize the covert transmit rate. Numerical results show that the proposed scheme outperforms the state of the art, i.e., the suboptimal Rand- AP scheme, by increasing the transmission rate by more than 23% while maintaining covertness and is better than the rest of the benchmark schemes.

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http://hdl.handle.net/10453/180210