Blind decision feedback equalizer with adaptive operation mode switching

Blind decision feedback equalizer with adaptive operation mode switching | 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 Blind decision feedback equalizer with adaptive operation mode switching Vladimir Krstić This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7741506/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract In this paper, a new operation mode switching method is proposed for a blind decision feedback equalizer (DFE) aiming to avoid the problems of using fixed performance threshold levels and thus provide a faster convergence rate. The operation mode switching based on a priori selected (fixed) performance thresholds is commonly done by trying different threshold levels which is not practical and implies a lack of efficiency. The use of fixed thresholds degrades the performance of blind equalizers because system parameters are unknown, and it can even lead to their convergence failure. In contrast, the new method, called the adaptive threshold method, switches the DFE operation modes by comparing the convergence state of the complete equalizer including both feedforward (FFF) and feedback (FBF) equalizers, with the convergence state of the FBF equalizer alone. In this scenario the convergence state of the complete equalizer is quantified by its output mean square error (MSE), while the convergence state of the FBF is quantified by a convex functional defined as the weighted sum of the kurtosis number of the given signal constellation and the a posteriori error of the FBF, with the weighting factor being a quantity inversely proportional to the correntropy coefficient of the FBF. Based on these two performance measures, the DFE switches operation modes by making the comparison between the output MSE and the convex functional which acts as an adaptive performance threshold level in respect of the MSE. The efficiency of the adaptive threshold method is evaluated by simulations using different QAM signals and equalization scenarios. The results of comparison tests between the adaptive threshold method and the one using fixed thresholds have shown the superiority of the proposed method. Blind decision feedback equalizer adaptive threshold method joint entropy maximization algorithm correntropy coefficient Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Dec, 2025 Reviews received at journal 27 Nov, 2025 Reviews received at journal 14 Nov, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 10 Oct, 2025 Reviews received at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 08 Oct, 2025 Reviewers invited by journal 08 Oct, 2025 Editor assigned by journal 08 Oct, 2025 Submission checks completed at journal 08 Oct, 2025 First submitted to journal 29 Sep, 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-7741506","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531721945,"identity":"f8921753-9fb4-44dc-a94b-e30e22ef06a9","order_by":0,"name":"Vladimir 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switching","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":"wireless-personal-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wire","sideBox":"Learn more about [Wireless Personal Communications](https://www.springer.com/journal/11277)","snPcode":"11277","submissionUrl":"https://submission.nature.com/new-submission/11277/3","title":"Wireless Personal Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Blind decision feedback equalizer, adaptive threshold method, joint entropy maximization algorithm, correntropy coefficient","lastPublishedDoi":"10.21203/rs.3.rs-7741506/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7741506/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this paper, a new operation mode switching method is proposed for a blind decision feedback equalizer (DFE) aiming to avoid the problems of using fixed performance threshold levels and thus provide a faster convergence rate. The operation mode switching based on a priori selected (fixed) performance thresholds is commonly done by trying different threshold levels which is not practical and implies a lack of efficiency. The use of fixed thresholds degrades the performance of blind equalizers because system parameters are unknown, and it can even lead to their convergence failure. In contrast, the new method, called the adaptive threshold method, switches the DFE operation modes by comparing the convergence state of the complete equalizer including both feedforward (FFF) and feedback (FBF) equalizers, with the convergence state of the FBF equalizer alone. In this scenario the convergence state of the complete equalizer is quantified by its output mean square error (MSE), while the convergence state of the FBF is quantified by a \u003cem\u003econvex functional\u003c/em\u003e defined as the weighted sum of the kurtosis number of the given signal constellation and the a posteriori error of the FBF, with the weighting factor being a quantity inversely proportional to the \u003cem\u003ecorrentropy coefficient\u003c/em\u003e of the FBF. Based on these two performance measures, the DFE switches operation modes by making the comparison between the output MSE and the convex functional which acts as an adaptive performance threshold level in respect of the MSE. The efficiency of the adaptive threshold method is evaluated by simulations using different QAM signals and equalization scenarios. The results of comparison tests between the adaptive threshold method and the one using fixed thresholds have shown the superiority of the proposed method.\u003c/p\u003e","manuscriptTitle":"Blind decision feedback equalizer with adaptive operation mode switching","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 12:51:56","doi":"10.21203/rs.3.rs-7741506/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-03T09:12:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-27T08:20:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-14T22:14:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102091562280684614885797144888454964550","date":"2025-10-14T02:39:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"310967144267954497245047208614647020642","date":"2025-10-11T03:10:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-09T18:20:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295753514498904257782649666919652312055","date":"2025-10-09T13:56:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210501407372249263111420652188269918277","date":"2025-10-09T09:53:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"155631600459799523297301651340494015419","date":"2025-10-09T08:57:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78056554360991599114251628565764923278","date":"2025-10-09T03:53:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-08T21:18:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-08T07:11:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-08T07:10:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Wireless Personal Communications","date":"2025-09-29T11:19:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"wireless-personal-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wire","sideBox":"Learn more about [Wireless Personal Communications](https://www.springer.com/journal/11277)","snPcode":"11277","submissionUrl":"https://submission.nature.com/new-submission/11277/3","title":"Wireless Personal Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"594b7e5b-86fa-43a0-a123-1cda3e0b4133","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-14T22:38:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-22 12:51:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7741506","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7741506","identity":"rs-7741506","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}