Optimizing 5G network management

Optimizing 5G network management | 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 Article Optimizing 5G network management Huijun Gao, Dongxu Lei, Songlin Zhuang, Baruch Barzel, Stefano Boccaletti This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4963495/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Sep, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Modern society takes connectivity for granted. We, therefore, rely quite heavily on our communication networks, both to sustain interpersonal connections, but also to support our technological infrastructure, e.g., health, power or transportation. This dependence will further strengthen as 5G technology becomes more pervasive and communication traffic sharply increases. It is, therefore, crucial to develop methods to optimize the efficiency and reliability of our ever-expanding networks. Such methods must account for the interplay between the static network infrastructure and the dynamic user connection preferences. The problem is that the user preferences arise from each individual’s mobility and communication patterns - data that are strictly protected by privacy concerns, and hence cannot be used for the network optimization. To address this challenge we develop CLUSTER, an interpretable Bayesian non-parametric framework, that uses aggregate, low resolution, user data, to detect user groups with predictably correlated connection patterns. We show that CLUSTER offers actionable insights on the network management, such as setting each base-station’s activation cycles, detecting critical stations and guiding the deployment of new stations. All, without violating user privacy. More broadly, CLUSTER illustrates a general approach to extract meaningful information from privacy protected data. Physical sciences/Physics/Statistical physics, thermodynamics and nonlinear dynamics/Complex networks Physical sciences/Physics/Statistical physics, thermodynamics and nonlinear dynamics/Statistical physics Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryInformation.pdf Cite Share Download PDF Status: Published Journal Publication published 26 Sep, 2025 Read the published version in Nature Communications → Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4963495","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":346211992,"identity":"99933503-0918-45f6-8865-04cfc0d22131","order_by":0,"name":"Huijun Gao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYBACA4YDQLLiAA+II0GCljMHeHhI0AIEjG0HGIjXYs54/OKHj/PuyNgzMB+8zcNgl0dQi2XDmWLJmdueAR3GlmzNw5BcTNhhB84kSPNuOwzUwmMmzcNwILGBCC3Jv3nngLTwfyNWy/Fj0rwNYFvYiLaFzXLGMaCWw2zGlnMMkonQcuP44xsfag7bs7c3P7zxpsKOsBYGiTMGEAYz2ASC6oGAv/0BMcpGwSgYBaNgJAMA2OM89DJFrUcAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-1865-7492","institution":"Research Institute of Intelligent Control and Systems, Harbin Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Huijun","middleName":"","lastName":"Gao","suffix":""},{"id":346211993,"identity":"877799dd-ce1f-48cf-9615-74d768eba50c","order_by":1,"name":"Dongxu Lei","email":"","orcid":"","institution":"Harbin Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Dongxu","middleName":"","lastName":"Lei","suffix":""},{"id":346211994,"identity":"e6fb98e4-2ad3-41aa-8f05-a98d165590f2","order_by":2,"name":"Songlin Zhuang","email":"","orcid":"","institution":"Yongjiang Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Songlin","middleName":"","lastName":"Zhuang","suffix":""},{"id":346211995,"identity":"08a3205a-832c-45a6-818c-7d13fa05c4c3","order_by":3,"name":"Baruch Barzel","email":"","orcid":"https://orcid.org/0000-0001-8862-4384","institution":"Bar-Ilan University","correspondingAuthor":false,"prefix":"","firstName":"Baruch","middleName":"","lastName":"Barzel","suffix":""},{"id":346211996,"identity":"c2b396cd-9355-46fa-b06b-ba8b9602b8ea","order_by":4,"name":"Stefano Boccaletti","email":"","orcid":"","institution":"CNR - Institute of Complex Systems,","correspondingAuthor":false,"prefix":"","firstName":"Stefano","middleName":"","lastName":"Boccaletti","suffix":""}],"badges":[],"createdAt":"2024-08-23 10:20:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4963495/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4963495/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-63504-0","type":"published","date":"2025-09-26T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":92304517,"identity":"f92a3ead-2e1f-49eb-bb2b-d9f2cf1e3001","added_by":"auto","created_at":"2025-09-27 07:07:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6673369,"visible":true,"origin":"","legend":"","description":"","filename":"Paper.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4963495/v1_covered_db66a315-694a-4a1b-93ef-0f354f55faec.pdf"},{"id":69042252,"identity":"f5e16a51-8318-4c3b-816e-cf1961db37f1","added_by":"auto","created_at":"2024-11-15 02:04:23","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":125692503,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4963495/v1/8738f8844d55278ce8c98557.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Optimizing 5G network management","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4963495/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4963495/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Modern society takes connectivity for granted. We, therefore, rely quite heavily on\r\nour communication networks, both to sustain interpersonal connections, but also to\r\nsupport our technological infrastructure, e.g., health, power or transportation. This\r\ndependence will further strengthen as 5G technology becomes more pervasive and\r\ncommunication traffic sharply increases. It is, therefore, crucial to develop methods\r\nto optimize the efficiency and reliability of our ever-expanding networks. Such\r\nmethods must account for the interplay between the static network infrastructure\r\nand the dynamic user connection preferences. The problem is that the user preferences\r\narise from each individual’s mobility and communication patterns - data\r\nthat are strictly protected by privacy concerns, and hence cannot be used for the\r\nnetwork optimization. To address this challenge we develop CLUSTER, an interpretable\r\nBayesian non-parametric framework, that uses aggregate, low resolution,\r\nuser data, to detect user groups with predictably correlated connection patterns.\r\nWe show that CLUSTER offers actionable insights on the network management,\r\nsuch as setting each base-station’s activation cycles, detecting critical stations and\r\nguiding the deployment of new stations. All, without violating user privacy. More\r\nbroadly, CLUSTER illustrates a general approach to extract meaningful information\r\nfrom privacy protected data.","manuscriptTitle":"Optimizing 5G network management","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-15 02:04:15","doi":"10.21203/rs.3.rs-4963495/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2b0bbb07-20ab-4606-a09c-4754242e446d","owner":[],"postedDate":"November 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":36707051,"name":"Physical sciences/Physics/Statistical physics, thermodynamics and nonlinear dynamics/Complex networks"},{"id":36707052,"name":"Physical sciences/Physics/Statistical physics, thermodynamics and nonlinear dynamics/Statistical physics"}],"tags":[],"updatedAt":"2025-09-27T07:07:12+00:00","versionOfRecord":{"articleIdentity":"rs-4963495","link":"https://doi.org/10.1038/s41467-025-63504-0","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-09-26 04:00:00","publishedOnDateReadable":"September 26th, 2025"},"versionCreatedAt":"2024-11-15 02:04:15","video":"","vorDoi":"10.1038/s41467-025-63504-0","vorDoiUrl":"https://doi.org/10.1038/s41467-025-63504-0","workflowStages":[]},"version":"v1","identity":"rs-4963495","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4963495","identity":"rs-4963495","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}