On the Complexity of Machine Learning based Algorithms for Intelligent Reflecting Surface aided Communication System: A Survey

On the Complexity of Machine Learning based Algorithms for Intelligent Reflecting Surface aided Communication System: A Survey | 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 Systematic Review On the Complexity of Machine Learning based Algorithms for Intelligent Reflecting Surface aided Communication System: A Survey Godwin Mruma Gadiel, Eva Ibrahim Shayo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7219828/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 The demand for high data rates for applications such as telemedicine and online gaming has fueled the application of mmWave in wireless communication to harness the high bandwidth that will support high data rate. If the scatterers are badly distributed in the propagation environment, the attenuation loss is large thus affecting the mmWave communication. Researchers have revealed that, the metasurface devices known as Intelligent Reflecting Surfaces (IRS), can be used to manipulate the propagation environment to achieve constructive interference to the intended user and destructive interference to none intended user. Consequently, increasing the received energy to the intended user, thus improving the system data rate. It can also be used for security by exploiting the destructive interference feature, where none intended users will receive almost no signal at all. In this work, we provide a summary of communication systems that are aided with IRS, while using machine learning methods to find the proper phase shift that maximizes the system performance. The summary is expected to inform the system developers on appropriate machine learning algorithm that can be chosen depending on their requirements. Specifically, the study presents an analysis of their computational complexity versus the number of IRS elements. The results shows that, more than $50 \%$ of the algorithm's computational complexity increases exponentially with the number of IRS elements. This shows that, there is a trade off on achieving high beamforming gain by IRS surface with large number of array and the affordable computational complexity of the algorithm. IRS Machine Learning mmWave Computational Complexity 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. 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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-7219828","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":491191465,"identity":"c664fa21-c9af-4d2b-86a3-fae3c641216f","order_by":0,"name":"Godwin Mruma Gadiel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYPACGwaGAyRqSYNrkSBWy2EStMiHnX0mdaPmfGLf+dMJDD9qGOrkGwhoMbydbiadc+x24swbuRsYe44xSDAS1DI7jU06h+124oYbvBsYeBsYJJgJOQyi5d+5xA3nz25g/AvUwkbQL9JALbltBxI3HMjdwAyyhYeQFgPpNGbr3L5kY5BfDssck5CcQdCW2WmMt3O+2cn2nT+78eGbGht+giFmcACJc4ComCRo5igYBaNgFIwCBgANjD6TAy3neQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-0212-1466","institution":"University of Dar Es Salaam","correspondingAuthor":true,"prefix":"","firstName":"Godwin","middleName":"Mruma","lastName":"Gadiel","suffix":""},{"id":491191466,"identity":"cd80f6e9-170f-47a8-b4c6-af0b0416cc8d","order_by":1,"name":"Eva Ibrahim Shayo","email":"","orcid":"https://orcid.org/0000-0002-5730-4115","institution":"University of Dar Es Salaam","correspondingAuthor":false,"prefix":"","firstName":"Eva","middleName":"Ibrahim","lastName":"Shayo","suffix":""}],"badges":[],"createdAt":"2025-07-26 08:45:10","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-7219828/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7219828/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87820668,"identity":"a83ef6ed-3fcf-402b-a350-13edc24b3e44","added_by":"auto","created_at":"2025-07-29 10:53:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":336602,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7219828/v1_covered_26c1cb65-400c-439d-bae7-e4a7a7f67d7f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eOn the Complexity of Machine Learning based Algorithms for Intelligent Reflecting Surface aided Communication System: A Survey\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Dar es Salaam","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":"IRS, Machine Learning, mmWave, Computational Complexity","lastPublishedDoi":"10.21203/rs.3.rs-7219828/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7219828/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe demand for high data rates for applications such as telemedicine and online gaming has fueled the application of mmWave in wireless communication to harness the high bandwidth that will support high data rate. 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