Green Communication Techniques for AI-Enhanced Resource Allocation in Future 6G Network

Green Communication Techniques for AI-Enhanced Resource Allocation in Future 6G Network | 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 Green Communication Techniques for AI-Enhanced Resource Allocation in Future 6G Network Kehinde Adeyinka, Qi Ming Huang, Taye Adeyinka This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6200135/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 This paper presents how integrating AI-driven algorithms for energy-efficient resource allocation in 6G networks can be one solution to meet the ever-growing demand for high-performance and sustainable wireless systems, focusing on green communication strategies. This proposed framework makes sure that the minimum energy consumption and maximum resource utilization through state-of-the-art machine learning techniques. It builds a mathematical model that suits the demands of the 6G network and involves tradeoffs between power efficiency, latency, and throughput. The different network situations include changes in traffic loads and environmental factors, which are modeled through MATLAB simulations to validate this approach. The results show very significant gains in energy efficiency, with up to 30% power use compared to traditional techniques at the same or even improved quality of communication. Several key findings show that AI can enable green communication without deteriorating system performance or user experience. This research also provides valuable recommendations for network operators and regulators on achieving carbon neutrality in the telecommunications industry and contributes to developing sustainable 6G technology. Green Communication AI-Driven Resource Allocation 6G Networks Energy Efficiency Machine Learning Sustainable Wireless Systems Full Text Additional Declarations No competing interests reported. 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-6200135","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452796689,"identity":"cfa7544f-41cf-43e4-98e6-e27793090ef2","order_by":0,"name":"Kehinde Adeyinka","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Kehinde","middleName":"","lastName":"Adeyinka","suffix":""},{"id":452796691,"identity":"f0e25aa6-cf98-4309-9d9d-a5f6bef3f71f","order_by":1,"name":"Qi Ming Huang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"Ming","lastName":"Huang","suffix":""},{"id":452796694,"identity":"32244fa1-0c69-40f7-9e8c-42fcfb6e211e","order_by":2,"name":"Taye Adeyinka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABHElEQVRIiWNgGAWjYFCCBBBKgLINbORA9IEHxGjhAbEfVKQZg7UkENLCANXC+ODMocQGuCAOwN+efEzi4Y40eXv2M4YPEtsOpM8PO/wQaIudnG4Ddi0SZ56lSSSeyTHs4ckxNkhsu5O78XaaAVBLsrHZARzW3Mgxk0hsq2DsYQAznuVunJ0A0nIgcRsOLfI38r+BtNj38L8x/5HYdjjdcHb6B7xaDG7ksAG15CT2SOSYMSScOZwgL52D3xbDM8+MLRLb0pJ7bjwrlkioSDPcIJ1TcCDBALdf5I4nP7z5sy3Ztr0/eePHHwY28vKz0zd/+FBhJ4fT+wwMLBIQmsMA4lSwSgOcykGA+QOEZn8ApuQb8KoeBaNgFIyCEQgAYyFr0kras2MAAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Taye","middleName":"","lastName":"Adeyinka","suffix":""}],"badges":[],"createdAt":"2025-03-11 04:38:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6200135/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6200135/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106925833,"identity":"57b269ab-c1ca-422a-bf26-7e74fc599a15","added_by":"auto","created_at":"2026-04-14 22:24:32","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":816838,"visible":true,"origin":"","legend":"","description":"","filename":"GreenCommunicationTechniquesforAIEnhancedResourceAllocationinFuture6GNetwork.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6200135/v1_covered_99ad728c-e40e-4ddb-94ae-6036627fde06.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Green Communication Techniques for AI-Enhanced Resource Allocation in Future 6G Network","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":"Green Communication, AI-Driven Resource Allocation, 6G Networks, Energy Efficiency, Machine Learning, Sustainable Wireless Systems","lastPublishedDoi":"10.21203/rs.3.rs-6200135/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6200135/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper presents how integrating AI-driven algorithms for energy-efficient resource allocation in 6G networks can be one solution to meet the ever-growing demand for high-performance and sustainable wireless systems, focusing on green communication strategies. This proposed framework makes sure that the minimum energy consumption and maximum resource utilization through state-of-the-art machine learning techniques. It builds a mathematical model that suits the demands of the 6G network and involves tradeoffs between power efficiency, latency, and throughput. The different network situations include changes in traffic loads and environmental factors, which are modeled through MATLAB simulations to validate this approach.\u003c/p\u003e \u003cp\u003eThe results show very significant gains in energy efficiency, with up to 30% power use compared to traditional techniques at the same or even improved quality of communication. Several key findings show that AI can enable green communication without deteriorating system performance or user experience. This research also provides valuable recommendations for network operators and regulators on achieving carbon neutrality in the telecommunications industry and contributes to developing sustainable 6G technology.\u003c/p\u003e","manuscriptTitle":"Green Communication Techniques for AI-Enhanced Resource Allocation in Future 6G Network","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-08 09:09:13","doi":"10.21203/rs.3.rs-6200135/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"7bcfa723-019a-4eab-8af6-f11d10fc2c6a","owner":[],"postedDate":"May 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-14T22:24:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-08 09:09:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6200135","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6200135","identity":"rs-6200135","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}