Enhanced Beam Training for Risassisted Terahertz Systems: Analysis Based on Quantized Phase Control

Enhanced Beam Training for Risassisted Terahertz Systems: Analysis Based on Quantized Phase Control | 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 Enhanced Beam Training for Risassisted Terahertz Systems: Analysis Based on Quantized Phase Control Emmanuel Ampoma Affum, Austin Kello This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8622131/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 Terahertz (THz) frequencies are of great interest due to their ultra-wide bandwidth and the need for ultra-reliable and high-capacity wireless communication in sixth-generation (6G) networks. However, THz signals’ effectiveness in practical applications is constrained by significant path loss, beam split effects, and alignment difficulties. A promising solution that makes wavefront control affordable and programmable is Reconfigurable Intelligent Surfaces (RIS). However, the majority of RIS-assisted beam training frameworks currently in use ignore real-world hardware constraints by assuming perfect continuous phase control or extremely low phase resolutions. In this paper, a quantization-aware beam training framework that explicitly accounts for the effects of finite phase resolution is proposed for RIS-assisted wideband THz systems. With an emphasis on intermediate quantization levels, specifically 3-bit and 4-bit control, the study creates and assesses algorithms that strike a balance between hardware viability and spectral efficiency. Simulation results show that the suggested 4-bit quantization-aware scheme outperforms conventional techniques like exhaustive search, multi-directional training, and the analytical Power Distribution Pattern (PDP)-based framework, achieving near-optimal performance in terms of achievable rate and beam training overhead. According to the results, 4-bit quantization offers a workable compromise between system performance and implementation complexity, demonstrating that scalable, high-throughput THz communications can be reliably supported by inexpensive RIS hardware. By bridging the gap between deployable RIS solutions and theoretical beam training designs, this work provides an effective route to the realization of RIS-enabled 6G networks. Terahertz communication reconfigurable intelligent surface beam training quantized phase control wideband OFDM 6G networks Full Text 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-8622131","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598184159,"identity":"bd807d69-d21b-45bb-8f5a-6cd10671df7d","order_by":0,"name":"Emmanuel Ampoma Affum","email":"","orcid":"","institution":"Kwame Nkrumah University of Science and Technology College of Engineering","correspondingAuthor":false,"prefix":"","firstName":"Emmanuel","middleName":"Ampoma","lastName":"Affum","suffix":""},{"id":598184160,"identity":"bc7d0dc3-127b-4dea-a7a7-0244d90ab76d","order_by":1,"name":"Austin Kello","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBACCQbmxgNgFjMD44MPQJqNnaAWxgawFh5mBmbDGSAtzERrASoW5oFYhx9Itjc2HPhQc9jenp33GLPNr23yfEAXfviYg1uLNM/BhoMzjh1O7GHmS3uc23fbsA3oQsmZ23BrkZNIbDjMw3Y4gYeZx9w4t+c2I1ALGzMvPi3yD4Fa/h22B2oxk7bsuW1PUIu0BGPDYd62w4w9IC0MP24nEtQi2ZPYcHBmX3piz2EeY8PehtvJbcyMzXj9InH88MEHH75Z27P3nzF88OPPbdv57c0HP3zEowUVMLaByQZi1YPAH1IUj4JRMApGwUgBALQfTtP1yW65AAAAAElFTkSuQmCC","orcid":"","institution":"Kwame Nkrumah University of Science and Technology College of Engineering","correspondingAuthor":true,"prefix":"","firstName":"Austin","middleName":"","lastName":"Kello","suffix":""}],"badges":[],"createdAt":"2026-01-16 20:59:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8622131/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8622131/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106724046,"identity":"5b88a1a4-2160-477f-bce7-e247442e3994","added_by":"auto","created_at":"2026-04-12 18:24:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1129182,"visible":true,"origin":"","legend":"","description":"","filename":"ENHANCEDBEAMTRAININGFORRISASSISTEDTERAHERTZSYSTEMS.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8622131/v1_covered_7047e570-4b09-41b4-972e-37d530a73cc9.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eEnhanced Beam Training for Risassisted Terahertz Systems: Analysis Based on Quantized Phase Control\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"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":"Terahertz communication, reconfigurable intelligent surface, beam training, quantized phase control, wideband OFDM, 6G networks","lastPublishedDoi":"10.21203/rs.3.rs-8622131/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8622131/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTerahertz (THz) frequencies are of great interest due to their ultra-wide bandwidth and the need for ultra-reliable and high-capacity wireless communication in sixth-generation (6G) networks. However, THz signals’ effectiveness in practical applications is constrained by significant path loss, beam split effects, and alignment difficulties. A promising solution that makes wavefront control affordable and programmable is Reconfigurable Intelligent Surfaces (RIS). However, the majority of RIS-assisted beam training frameworks currently in use ignore real-world hardware constraints by assuming perfect continuous phase control or extremely low phase resolutions.\u003c/p\u003e\n\u003cp\u003eIn this paper, a quantization-aware beam training framework that explicitly accounts for the effects of finite phase resolution is proposed for RIS-assisted wideband THz systems. With an emphasis on intermediate quantization levels, specifically 3-bit and 4-bit control, the study creates and assesses algorithms that strike a balance between hardware viability and spectral efficiency. 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