Multi‑User Subscriber Identification Using Turbo Codes on Programmable Radio Platforms

Multi‑User Subscriber Identification Using Turbo Codes on Programmable Radio Platforms | 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 Multi‑User Subscriber Identification Using Turbo Codes on Programmable Radio Platforms Serhii Liventsev This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9556780/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper proposes a method for subscriber identification in a multi-user unidirectional data transmission system based on software-defined radio (SDR). Unlike conventional approaches relying on protocol-level signaling or cryptographic mechanisms, the proposed method operates at the physical layer by exploiting structural parameters of turbo codes (TC), including block length, coding rate, interleaver type, and generator polynomial. The identification problem is formulated as a sequential parameter estimation task and implemented through a three-stage algorithm comprising channel data separation, interleaver detection, and iterative decoding-based parameter inference. A mathematical model describing identification complexity and reliability is developed, including analytical approximations of the average number of decoding iterations under varying signal-to-noise ratio (SNR) conditions. Simulation results demonstrate that the proposed method ensures reliable subscriber identification in low-SNR and impulsive interference environments, while reducing identification overhead to 10–15% of the total decoding time. The approach enables implicit identification without modifying transmission protocols and can be integrated into SDR-based multi-user systems, including 5G NR scenarios. The proposed solution provides a unified mechanism for combining error-correcting coding and subscriber identification, improving system efficiency, robustness, and security. The method can be interpreted as a constrained optimization problem over the space of turbo code configurations. Cell Communication and Signaling Artificial Intelligence and Machine Learning Electrical Engineering Cognitive radio turbo codes subscriber identification software-defined radio (SDR) multi-user systems interference robustness iterative decoding 5G NR Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted 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-9556780","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":631235787,"identity":"38a024e1-68e6-4b94-9f15-b1fc91978294","order_by":0,"name":"Serhii Liventsev","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYDACdsYGKANEG1gQoYUZpoXnAEiLBDFaYAyJBDBJWId8M3ObxMcddnIGN59f3fCjQIKBv707Aa8Wg8OMbZIzzyQbG9zOKbvZA3SYxJmzG/BrYWZsNuZtO5A4c3ZO2g0eoBYDiVz8WuSbgVr+th2onznzTNrNP8RoYTjM2PiYse1AAr8E+7HbRNkC9Evjw962ZMN+nhy22zIGEjwE/SLf3v7gwM82O3k29uPPbr75YyPH395LwGEIwGMAJolVDgLsD0hRPQpGwSgYBSMIAADpbkSteRZ+0AAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-9768-8133","institution":"National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”,","correspondingAuthor":true,"prefix":"","firstName":"Serhii","middleName":"","lastName":"Liventsev","suffix":""}],"badges":[],"createdAt":"2026-04-28 16:45:21","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-9556780/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9556780/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108492026,"identity":"7c5fdc15-d7ac-4a7b-ba41-42a686e3c67d","added_by":"auto","created_at":"2026-05-05 09:56:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":621920,"visible":true,"origin":"","legend":"","description":"","filename":"Liventsevv2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9556780/v1_covered_1a1226ca-9f5c-468b-aaf8-e28b35e35b93.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eMulti‑User Subscriber Identification Using Turbo Codes on Programmable Radio Platforms\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”,","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cognitive radio, turbo codes, subscriber identification, software-defined radio (SDR), multi-user systems, interference robustness, iterative decoding, 5G NR","lastPublishedDoi":"10.21203/rs.3.rs-9556780/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9556780/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper proposes a method for subscriber identification in a multi-user unidirectional data transmission system based on software-defined radio (SDR). 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