Quantized Event-Triggered Resilient Filtering for Bandwidth-Limited Wireless Sensor Networks

Quantized Event-Triggered Resilient Filtering for Bandwidth-Limited Wireless Sensor Networks | 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 Quantized Event-Triggered Resilient Filtering for Bandwidth-Limited Wireless Sensor Networks Haoliang Guan, Xiaoqi Lu, Yuanyuan Chi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9308838/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Wireless sensor networks (WSNs) operate over bandwidth- and energy-limited wireless links, so remote estimation algorithms must jointly balance communication burden, estimation accuracy, and resilience against abnormal measurements. This paper presents a quantized event-triggered (QET) resilient filtering framework for centralized state estimation with explicit finite-bit innovation packets. At the default operating point, each triggered two-dimensional innovation is encoded into a 16-bit packet, and the corresponding average transmissions per sensor is about 0.45 packets per step. Each sensor transmits only when its local innovation exceeds a triggering threshold, and the triggered innovation is encoded by a saturating finite-level uniform quantizer before transmission to the fusion center. To improve robustness under bias attacks and gross faults, the fusion center applies a normalized innovation squared (NIS) gate together with quantization-aware covariance inflation before a Kalman-type update. The main contribution is not a new gate in isolation, but a reproducible design-and-validation pipeline for bandwidth-limited WSNs: we make the packet budget explicit, formalize attack models, analyze lightweight implementation cost, and examine the coupling between the triggering threshold and quantization step. Simulations on a motion-tracking benchmark show that the proposed method preserves competitive estimation accuracy in a finite-bit low-bandwidth regime, while the empirical quantization study indicates that the white-noise approximation remains reliable for roughly $\Delta \le 0.8$. Under sensor bias attacks, the gated resilient extension bounds the steady-state RMSE markedly better than the unprotected finite-bit baseline, while a stealthy ramp attack clarifies the limits of lightweight memoryless gating and motivates future adaptive defenses. Physical sciences/Engineering Physical sciences/Mathematics and computing Physical sciences/Physics wireless sensor networks event-triggered communication quantized innovation finite-bit packet resilient filtering Kalman filtering attack-resilient sensing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 16 May, 2026 Reviewers agreed at journal 18 Apr, 2026 Reviewers invited by journal 13 Apr, 2026 Editor assigned by journal 13 Apr, 2026 Editor invited by journal 10 Apr, 2026 Submission checks completed at journal 07 Apr, 2026 First submitted to journal 07 Apr, 2026 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-9308838","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":625582921,"identity":"480e0125-3fa6-4e76-998b-35255b771b80","order_by":0,"name":"Haoliang Guan","email":"","orcid":"","institution":"Inner Mongolia University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Haoliang","middleName":"","lastName":"Guan","suffix":""},{"id":625582922,"identity":"53c2f754-da0d-4d30-a305-f53b35570312","order_by":1,"name":"Xiaoqi Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBACPgbGBiAlIccG4TMT1sIG1WIM1AJiEaUFAhIbiNcikdz44UOZRXqf2BnzBwwV1okN7GcP4NfCc7BZcsY5idw26RzDBoYz6YkNPHkJ+LWwNzZI87ZBtTC2HU5skOAxwK+FmbH5N1BLOhtYyz9itLA3toFsSYBoaSBGC8/BNkugXwzbpNMKZyQcSzdu48nBr4VfIv3xjQ9ldfLys5M3fPhQYy3bz34GvxaoXVA6AYlNpJZRMApGwSgYBdgAAK0tO5DY5RqDAAAAAElFTkSuQmCC","orcid":"","institution":"Inner Mongolia University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Xiaoqi","middleName":"","lastName":"Lu","suffix":""},{"id":625582923,"identity":"1ca37c4f-8de7-4037-b737-f3f2cf323df1","order_by":2,"name":"Yuanyuan Chi","email":"","orcid":"","institution":"Baotou Vocational and Technical College","correspondingAuthor":false,"prefix":"","firstName":"Yuanyuan","middleName":"","lastName":"Chi","suffix":""}],"badges":[],"createdAt":"2026-04-03 04:53:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9308838/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9308838/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107484297,"identity":"1a4dff35-49ed-4c1b-b4ef-54cd55b7eb90","added_by":"auto","created_at":"2026-04-22 02:31:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":396541,"visible":true,"origin":"","legend":"","description":"","filename":"manuscriptrevised.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9308838/v1_covered_8a56319e-942c-4025-8be6-7e69dac81a2a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantized Event-Triggered Resilient Filtering for Bandwidth-Limited Wireless Sensor Networks","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"wireless sensor networks, event-triggered communication, quantized innovation, finite-bit packet, resilient filtering, Kalman filtering, attack-resilient sensing","lastPublishedDoi":"10.21203/rs.3.rs-9308838/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9308838/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Wireless sensor networks (WSNs) operate over bandwidth- and energy-limited wireless links, so remote estimation algorithms must jointly balance communication burden, estimation accuracy, and resilience against abnormal measurements. This paper presents a quantized event-triggered (QET) resilient filtering framework for centralized state estimation with explicit finite-bit innovation packets. At the default operating point, each triggered two-dimensional innovation is encoded into a 16-bit packet, and the corresponding average transmissions per sensor is about 0.45 packets per step. Each sensor transmits only when its local innovation exceeds a triggering threshold, and the triggered innovation is encoded by a saturating finite-level uniform quantizer before transmission to the fusion center. To improve robustness under bias attacks and gross faults, the fusion center applies a normalized innovation squared (NIS) gate together with quantization-aware covariance inflation before a Kalman-type update. The main contribution is not a new gate in isolation, but a reproducible design-and-validation pipeline for bandwidth-limited WSNs: we make the packet budget explicit, formalize attack models, analyze lightweight implementation cost, and examine the coupling between the triggering threshold and quantization step. Simulations on a motion-tracking benchmark show that the proposed method preserves competitive estimation accuracy in a finite-bit low-bandwidth regime, while the empirical quantization study indicates that the white-noise approximation remains reliable for roughly $\\Delta \\le 0.8$. Under sensor bias attacks, the gated resilient extension bounds the steady-state RMSE markedly better than the unprotected finite-bit baseline, while a stealthy ramp attack clarifies the limits of lightweight memoryless gating and motivates future adaptive defenses.","manuscriptTitle":"Quantized Event-Triggered Resilient Filtering for Bandwidth-Limited Wireless Sensor Networks","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-20 05:46:18","doi":"10.21203/rs.3.rs-9308838/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"291700353700843389425684940338971591480","date":"2026-05-16T08:14:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324302187361430590677424510328489566057","date":"2026-04-19T02:20:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-13T07:49:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T07:40:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-10T05:53:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-08T02:46:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-04-08T02:40:43+00:00","index":"","fulltext":""}],"status":"published","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}}],"origin":"","ownerIdentity":"559e7493-c639-4a86-a6c7-097d76d9ba69","owner":[],"postedDate":"April 20th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"291700353700843389425684940338971591480","date":"2026-05-16T08:14:20+00:00","index":75,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66586974,"name":"Physical sciences/Engineering"},{"id":66586975,"name":"Physical sciences/Mathematics and computing"},{"id":66586976,"name":"Physical sciences/Physics"}],"tags":[],"updatedAt":"2026-04-20T05:46:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-20 05:46:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9308838","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9308838","identity":"rs-9308838","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}