Information timeliness aware multispectral integrated sensing, communication, and computing for high-voltage discharge detection

Liao, H, Yao, Z, Lu, J, Shu, Y, Zhou, Z and Mumtaz, S ORCID: https://orcid.org/0000-0001-6364-6149, 2024. Information timeliness aware multispectral integrated sensing, communication, and computing for high-voltage discharge detection. IEEE Transactions on Communications. ISSN 0090-6778

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Abstract

The application of multispectral image based partial discharge detection offers a dependable solution for high-voltage substations. Captured visible light and ultraviolet (UV) images are denoised, transmitted and fused to enhance detection performance. However, existing approaches separately design the sensing-layer image denoising, communication-layer image transmission, and computing-layer image fusion, and the lack of unified cooperation hinders the overall performance. To address this issue, it is crucial to integrate sensing, communication, and computing to improve detection accuracy and timeliness. In this paper, we formulate a timeliness and accuracy joint guarantee problem, which aims to minimize the weighted sum of peak age of information (AoI), false-positive detection ratio, and false-negative detection ratio by jointly optimizing sensing-layer filtering window size, communication-layer time division ratio, and computing layer wavelet decomposition level. We propose a multispectral integrated sensing, communication, and computing algorithm based on AoI and false-negative aware multi-experience replay cooperative learning to solve the problem. Simulation results demonstrate that the proposed algorithm outperforms existing methods in terms of peak AoI, false-positive detection ratio, false-negative detection ratio, and convergence speed.

Item Type:	Journal article
Publication Title:	IEEE Transactions on Communications
Creators:	Liao, H., Yao, Z., Lu, J., Shu, Y., Zhou, Z. and Mumtaz, S.
Publisher:	Institute of Electrical and Electronics Engineers
Date:	11 June 2024
ISSN:	0090-6778
Identifiers:	Number Type 10.1109/tcomm.2024.3412773 DOI 1904120 Other
Rights:	© 2024 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.
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	18 Jun 2024 07:44
Last Modified:	18 Jun 2024 07:44
URI:	https://irep.ntu.ac.uk/id/eprint/51577

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