Joint Channel Estimation and Feedback with Masked Token Transformers in Massive MIMO Systems

Joint Channel Estimation and Feedback with Masked Token Transformers in Massive MIMO Systems | 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 Joint Channel Estimation and Feedback with Masked Token Transformers in Massive MIMO Systems Mei Yin, Mingming Zhao, Lin Liu, Lifu Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6717894/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Channel estimation constitutes a pivotal concern within the realm of practical massive multiple-input multiple-output (MIMO) systems. Recently, numerous studies have been conducted to harness the power of deep neural networks for better channel estimation and feedback. However, they often overlook a crucial factor: the intrinsic correlation features present in downlink channel state information (CSI). As a consequence, in challenging environments, the performance of channel estimation and feedback frequently falls short of expectations. To achieve joint channel estimation and feedback, this paper proposes an encoder-decoder based network that unveils the intrinsic frequency-domain correlation within the CSI matrix. The entire encoder-decoder network is utilized for channel compression. To efficiently capture and reconstruct correlation features, we propose a self-mask-attention coding mechanism, augmented by an active masking strategy aimed at enhancing operational efficiency. Besides, this paper employs a streamlined multilayer perceptron denoising module to achieve more precise estimations in the decoder part for channel estimation. Extensive experiments demonstrate that our method not only outperforms state-of-the-art channel estimation and feedback techniques in joint tasks but also achieves beneficial performance in individual tasks. Physical sciences/Mathematics and computing/Computer science Physical sciences/Mathematics and computing/Information technology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 07 Jul, 2025 Reviews received at journal 29 Jun, 2025 Reviews received at journal 29 Jun, 2025 Reviewers agreed at journal 19 Jun, 2025 Reviewers agreed at journal 14 Jun, 2025 Reviewers invited by journal 11 Jun, 2025 Editor assigned by journal 11 Jun, 2025 Editor invited by journal 02 Jun, 2025 Submission checks completed at journal 31 May, 2025 First submitted to journal 21 May, 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. 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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-6717894","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":470258436,"identity":"4bb5a2f2-d792-4798-a960-ab8bfb562e4d","order_by":0,"name":"Mei Yin","email":"","orcid":"","institution":"Changzhou Institute of Mechatronic Technology","correspondingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Yin","suffix":""},{"id":470258437,"identity":"82726f08-28ec-4e1b-9d5a-847023492555","order_by":1,"name":"Mingming Zhao","email":"","orcid":"","institution":"Beihang University","correspondingAuthor":false,"prefix":"","firstName":"Mingming","middleName":"","lastName":"Zhao","suffix":""},{"id":470258438,"identity":"5b3c9e20-b579-4b8e-a27a-9e8b3d513b74","order_by":2,"name":"Lin Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYBACPnbGxgcf/9gwMDAzN8AEDfBqYWNmPmw4syENqIWxAaaakBa2NGnehsNAJvFaeIwNeHecj+ZvZ2xg5vnzR56BvXmbBEPNHXxaDB9InrmdO+MwUAtvm4FhA8+xMgmGY8/w22LAdju3AaylwSCBQSLHTIIR7FScWswkEtjO5c4/DHYYUIv8G0Ja2NIkDrYdyN0A1sIGsoWHkBZgIDecSc7dCNRycG6bsWEbT1qxRcIx3Fr42RsbH/+psMudd/7wwQdv/sjJ87Mf3njjQw1uLSjgANheEJFAnIZRMApGwSgYBTgAABelTYzrHNIRAAAAAElFTkSuQmCC","orcid":"","institution":"University of Science and Technology of China","correspondingAuthor":true,"prefix":"","firstName":"Lin","middleName":"","lastName":"Liu","suffix":""},{"id":470258439,"identity":"b86204f6-6259-4114-bc09-a67efe1b7af9","order_by":3,"name":"Lifu Liu","email":"","orcid":"","institution":"Huawei Technologies (China)","correspondingAuthor":false,"prefix":"","firstName":"Lifu","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-05-21 15:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6717894/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6717894/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-25256-1","type":"published","date":"2025-11-24T15:58:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":97179654,"identity":"e073ff39-5a6d-40f3-8e3b-651a742914b2","added_by":"auto","created_at":"2025-12-01 16:16:35","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":583095,"visible":true,"origin":"","legend":"","description":"","filename":"ScientificReports.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6717894/v1_covered_9712963a-68ff-4b9f-a13b-b4224c1d1cd8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Joint Channel Estimation and Feedback with Masked Token Transformers in Massive MIMO Systems","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6717894/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6717894/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Channel estimation constitutes a pivotal concern within the realm of practical massive multiple-input multiple-output (MIMO) systems. 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