An Innovative Noise Reduction Algorithm for 5G Millimeter-Wave Monitoring of Urban Bridge Micro-Deformation

An Innovative Noise Reduction Algorithm for 5G Millimeter-Wave Monitoring of Urban Bridge Micro-Deformation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An Innovative Noise Reduction Algorithm for 5G Millimeter-Wave Monitoring of Urban Bridge Micro-Deformation Haiqian Wu, Runjie Wang, Xianglei Liu, Liang Huo, Ming Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6866300/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract The monitoring of urban bridge micro-deformation is crucial for ensuring the safe operation of bridge, preventing disasters, and improving construction efficiency. However, existing monitoring methods face challenges such as difficult deployment, maintenance, low precision, and low frequency, making it hard to obtain dynamic deflection data of urban bridge. In recent years, millimeter waves emitted and received by 5G base stations, with their non-contact, high-frequency, and 7×24 all-day advantages, have begun to be applied to the high-dynamic monitoring of urban bridge dynamic deflection. Nevertheless, 5G millimeter wave monitoring is susceptible to noise due to complex environmental factors, leading to unreliable dynamic deflection information of bridge. Therefore, based on the analysis of noise sources and propagation characteristics in the monitoring process, this paper proposes an Improved Second Order Blind Identification (I-SOBI) algorithm to enhance the accuracy of 5G millimeter wave monitoring by mitigating the issues caused by the linear correlation of original signals. The I-SOBI algorithm can recover source signals from noisy ones that exhibit nonlinear characteristics or are non-Gaussian distributed. It not only preserves the contribution of useful information from the separated signals during the reconstruction process but also achieves the goal of reducing the impact of noisy components on the reconstructed results. Furthermore, through simulation experiments and practical experiments applying 5G millimeter wave monitoring to bridge dynamic deflection, the effectiveness and feasibility of this method are verified. The research methods presented in this paper can improve the accuracy of 5G millimeter wave monitoring for urban bridge dynamic deflection, providing a reliable basis for structural health assessment. 5G Millimeter Wave Monitoring Urban bridge Micro-deformation Noise Reduction Improved Second Order Blind Identification Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 Jul, 2025 Reviews received at journal 01 Jul, 2025 Reviews received at journal 01 Jul, 2025 Reviews received at journal 29 Jun, 2025 Reviewers agreed at journal 18 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers invited by journal 17 Jun, 2025 Editor assigned by journal 17 Jun, 2025 Submission checks completed at journal 16 Jun, 2025 First submitted to journal 10 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6866300","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":473162856,"identity":"1c76743d-8bc1-40f6-9cfa-1eee7f902b81","order_by":0,"name":"Haiqian Wu","email":"","orcid":"","institution":"Beijing University of Civil Engineering and Architecture","correspondingAuthor":false,"prefix":"","firstName":"Haiqian","middleName":"","lastName":"Wu","suffix":""},{"id":473162857,"identity":"bc577980-95cf-4057-a9e5-03457a2263c8","order_by":1,"name":"Runjie 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However, existing monitoring methods face challenges such as difficult deployment, maintenance, low precision, and low frequency, making it hard to obtain dynamic deflection data of urban bridge. In recent years, millimeter waves emitted and received by 5G base stations, with their non-contact, high-frequency, and 7\u0026times;24 all-day advantages, have begun to be applied to the high-dynamic monitoring of urban bridge dynamic deflection. Nevertheless, 5G millimeter wave monitoring is susceptible to noise due to complex environmental factors, leading to unreliable dynamic deflection information of bridge. Therefore, based on the analysis of noise sources and propagation characteristics in the monitoring process, this paper proposes an Improved Second Order Blind Identification (I-SOBI) algorithm to enhance the accuracy of 5G millimeter wave monitoring by mitigating the issues caused by the linear correlation of original signals. 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