Adaptive Spectrum Sensing and Management in Cognitive Radio Networks Using Federated Deep Reinforcement Learning

Adaptive Spectrum Sensing and Management in Cognitive Radio Networks Using Federated Deep Reinforcement Learning | 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 Adaptive Spectrum Sensing and Management in Cognitive Radio Networks Using Federated Deep Reinforcement Learning Dr. M.Saraswathi, Dr. D.Lakshminarayana, Mrs. P.Vaishnavidevi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7585019/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 dynamic and unexpected character of settings in wireless communication calls for sophisticated spectrum sensing techniques for cognitive radio networks. Building on the work of earlier ensemble machine learning approaches, this study presents a state-of-the-art framework for real-time spectrum management using federated deep reinforcement learning (FDRL). The combination of reinforcement learning's strategic decision-making process with Deep Belief Networks' (DBN) and Long Short-Term Memory's (LSTM) architectures is at the heart of this methodology. This approach, which operates inside a federated learning paradigm, gives user privacy and data locality, guaranteeing a reliable and private solution. Through processing signal vectors under different noise situations, the FDRL model repeatedly learns the best spectrum allocation strategies, improving its comprehension over time. This novel approach offers effective adaptability to the ever-changing wireless environment, improving network speed and spectrum utilization while protecting user privacy. Effectively separating idle from active channels, it continuously adjusts to variations in signal-to-noise ratios and user demands. This sophisticated technology is shown through thorough simulations to provide a significant improvement in both spectrum efficiency and user throughput. Because of its scalability and decentralization, it presents a viable answer to the changing wireless network environment, which is marked by an increasing need for autonomy and data-driven operations. This approach's proven ability to reduce interference and improve service quality indicates a major step forward for intelligent and autonomous spectrum sensing methods, which are critical in the age of ubiquitous wireless communication. The suggested FDRL-DBN-LSTM approach was implemented in Python and achieves an accuracy of 98.4%. Spectrum sensing Cognitive radio networks Federated deep reinforcement learning DBN LSTM 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-7585019","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":527443402,"identity":"2d2f3ec3-b4ad-46a2-a91d-defef4c46a89","order_by":0,"name":"Dr. M.Saraswathi","email":"","orcid":"","institution":"Panimalar Engineering College","correspondingAuthor":false,"prefix":"Dr.","firstName":"","middleName":"","lastName":"M.Saraswathi","suffix":""},{"id":527443403,"identity":"50645f50-36f1-433f-9f6a-809633737f10","order_by":1,"name":"Dr. D.Lakshminarayana","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYBACAwY2BmYIg8HwQYIBmxyIc+ABkVqMDT4U8BmDtSQQqcVMcsYHucQGEA+vFvZjyZ8Lc+zyzCWSN0jzGJilzw87/BBoi52cbgMOLTxpx6RnbksutpyRVmDMY5CWu/F2mgFQS7Kx2QFcDktvY+bdxpy44UaOQTKPwbHcjbMTQFoOJG7DpYX/efNn3m31YC2HeQz+pxvOTv+AX4tE2gFp3m2HQVoMG2cYsCXIS+cQsEXiWRpQy/HEDWeeFTN8MGAz3CCdU3AgwQC3X+z704yBDqtO3HA8efuPhD9s8vKz0zd/+FBhJ4dLCwIIJEDtPQAJFiIAP9RQ+QZiVI+CUTAKRsFIAgBNUmVZI6/dDwAAAABJRU5ErkJggg==","orcid":"","institution":"Chaitanya Deemed to be University","correspondingAuthor":true,"prefix":"Dr.","firstName":"","middleName":"","lastName":"D.Lakshminarayana","suffix":""},{"id":527443404,"identity":"cd624ecc-9375-47e9-a6a0-74be300d6848","order_by":2,"name":"Mrs. P.Vaishnavidevi","email":"","orcid":"","institution":"VidyaJyothi Institute of Technology","correspondingAuthor":false,"prefix":"Mrs.","firstName":"","middleName":"","lastName":"P.Vaishnavidevi","suffix":""}],"badges":[],"createdAt":"2025-09-10 16:53:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7585019/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7585019/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93529351,"identity":"39b50b6a-fcf3-4746-a094-1ec7ff3c763e","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1056453,"visible":true,"origin":"","legend":"","description":"","filename":"AdaptiveSpectrum.docx","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/071d8cd684c7ab286d77ebb4.docx"},{"id":93530784,"identity":"f3fb7622-4161-4c38-b567-e7479a97d01b","added_by":"auto","created_at":"2025-10-14 21:06:29","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6390,"visible":true,"origin":"","legend":"","description":"","filename":"7579db25a921478d9246c25a7b17fac6.json","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/cf8a4adbcbf742bb7645472f.json"},{"id":93530576,"identity":"753bb58e-e64a-4dae-9255-c7b69b31916f","added_by":"auto","created_at":"2025-10-14 20:58:29","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126809,"visible":true,"origin":"","legend":"","description":"","filename":"7579db25a921478d9246c25a7b17fac61enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/157d6fac37fcd029f889d011.xml"},{"id":93530581,"identity":"19c03a59-0282-4d20-9f59-6077a05a2eb0","added_by":"auto","created_at":"2025-10-14 20:58:29","extension":"eps","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":178886,"visible":true,"origin":"","legend":"","description":"","filename":"drawingimage1.eps","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/d2ccb720edd9234f4398c69b.eps"},{"id":93530785,"identity":"a1386505-42ff-483d-bd8b-6d7a7bb702f7","added_by":"auto","created_at":"2025-10-14 21:06:29","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":142661,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/8ce7c983a8263cf3c14597ef.jpeg"},{"id":93530573,"identity":"c293c1c6-0110-4f44-a075-31175dfefb01","added_by":"auto","created_at":"2025-10-14 20:58:29","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":87779,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/95164e56652a27e2970d3433.png"},{"id":93529347,"identity":"b231e8c6-7178-4029-b486-c3053538ca1e","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":40945,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/6756047aea875e9dfa065d02.png"},{"id":93531024,"identity":"a1763cc9-9ca9-4702-8521-b053594ff05e","added_by":"auto","created_at":"2025-10-14 21:14:29","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":25634,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/963b718fca109f3df6189775.png"},{"id":93529355,"identity":"479a6e84-98f6-45ed-b6ec-dfc4de1ad9da","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":33701,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage13.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/c72df379f8dda9fc6e2f074e.png"},{"id":93531025,"identity":"60ca6754-3909-431e-8c85-77b620e71bd7","added_by":"auto","created_at":"2025-10-14 21:14:29","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32644,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/f2395220f83467ee103df155.png"},{"id":93530579,"identity":"863528cd-60b6-49c0-b9a3-5dc64070ad39","added_by":"auto","created_at":"2025-10-14 20:58:29","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32975,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage15.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/7bd0e61e1b75cbbb16839599.png"},{"id":93530580,"identity":"adfda69b-65c6-4536-93d2-592696b1538e","added_by":"auto","created_at":"2025-10-14 20:58:29","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":33069,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage16.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/d5d618862bdee9ae6ca615e0.png"},{"id":93529374,"identity":"40e06c51-3b93-44e1-a203-36fc8f553fb1","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":70198,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/9649deaeb62a9650713d1b9f.png"},{"id":93530586,"identity":"469232e8-ea88-411d-973b-6ebcb06dd900","added_by":"auto","created_at":"2025-10-14 20:58:30","extension":"jpeg","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":141109,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/dce710e460757b8445b3e6e1.jpeg"},{"id":93530788,"identity":"cbbbc286-4b50-4dd3-bfe6-124e93409532","added_by":"auto","created_at":"2025-10-14 21:06:29","extension":"jpeg","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":139204,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/0c25f07c234f618254d710af.jpeg"},{"id":93529367,"identity":"2543b30b-3547-4e70-a7d7-0e55abd291a8","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"jpeg","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":93873,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/1e0d1260fef6e04dcdee1cd9.jpeg"},{"id":93529357,"identity":"c0d45325-1844-47c5-b64c-7c59c8fb7b20","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14721,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/8184639a1f32865402d6648e.png"},{"id":93529359,"identity":"c89ceeb6-d642-4563-829b-23c54e420090","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":54942,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/f1ef82917877b97cb495a977.png"},{"id":93530587,"identity":"3ffc2d3f-6138-459d-adee-6b1732aca59e","added_by":"auto","created_at":"2025-10-14 20:58:30","extension":"jpeg","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":571764,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/53c0d57040ea8e8924d2a97d.jpeg"},{"id":93530585,"identity":"82ffc588-5720-4485-9ef2-43c9e408b4fa","added_by":"auto","created_at":"2025-10-14 20:58:30","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16711,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/4631f66a926163148c62a90f.png"},{"id":93529362,"identity":"9782346f-4202-4487-934c-3a6b2ac28f54","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":27042,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/2f9e1b98b639dacfdc1b1fb8.png"},{"id":93529368,"identity":"0498463e-9661-4474-b3fb-26a61a73c56e","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":46535,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/d7f0652546cac54c089d2fc9.png"},{"id":93529375,"identity":"c9a1a2fe-80fb-4c1b-a0ff-52a669013276","added_by":"auto","created_at":"2025-10-14 20:50:30","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":20490,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/7c4bc9e7b80710320fcbd698.png"},{"id":93529363,"identity":"f66a31db-6f71-4d46-a259-55f9b2b7083e","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12474,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/e5b9481b571f9ca3624a7b35.png"},{"id":93530584,"identity":"16dd38fc-fd77-4a39-8f0b-4061c5bb1622","added_by":"auto","created_at":"2025-10-14 20:58:29","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8094,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/763d379af1a0690003afe399.png"},{"id":93529377,"identity":"67898db9-d6fc-4321-9635-e9d5bbf2fde2","added_by":"auto","created_at":"2025-10-14 20:50:30","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11288,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage13.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/144926a59e6404a37d4df90d.png"},{"id":93529366,"identity":"1a1d660d-293a-4ed7-a3be-96e386d94d03","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10857,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/72c6b41a1e5dee91ee05459b.png"},{"id":93529365,"identity":"ff001d70-e62f-4d53-864c-144e2bcba24f","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10962,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage15.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/7a36b92174fe00ab41a5dd0e.png"},{"id":93529386,"identity":"0e8b66b9-a3ec-4473-917e-20ae048b6e24","added_by":"auto","created_at":"2025-10-14 20:50:30","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10770,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage16.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/8ded383e41b12a38658d036f.png"},{"id":93529372,"identity":"4e5c9df1-fc75-4d3d-a27d-cde70375a11b","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":18023,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/1ffde17bf3200c73224bd5ca.png"},{"id":93529369,"identity":"736cf032-6fe2-4097-9b8c-5dfed3436519","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":63210,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/ed5569096d629e689195bd08.png"},{"id":93529388,"identity":"933a0c1c-6d2d-4e21-8b3f-da718717a574","added_by":"auto","created_at":"2025-10-14 20:50:30","extension":"png","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":85365,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/23c0a33db292bdbd08aa011e.png"},{"id":93530583,"identity":"735affa8-5418-4ce4-b0dc-01ff6cb63822","added_by":"auto","created_at":"2025-10-14 20:58:29","extension":"png","order_by":32,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":46766,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/31aa5bf289f38423197b9a0e.png"},{"id":93529376,"identity":"0bebaa90-e6c8-40ab-8c40-d7bf9cbde437","added_by":"auto","created_at":"2025-10-14 20:50:30","extension":"png","order_by":33,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5667,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/90a85e16758aea352392fb45.png"},{"id":93529387,"identity":"6cdbfbc0-6691-4606-8c3b-b0d7ad3ae576","added_by":"auto","created_at":"2025-10-14 20:50:30","extension":"png","order_by":34,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":15239,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/552a0c66e5b7c01bc9ab1055.png"},{"id":93530592,"identity":"a0fb5380-5fcd-4c2d-8ca8-aa6b9edbb603","added_by":"auto","created_at":"2025-10-14 20:58:30","extension":"png","order_by":35,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":107279,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/e4962469a17ba78d44bae485.png"},{"id":93529373,"identity":"9f6ec55e-56d8-4cae-b2f7-bbcf24b7aeff","added_by":"auto","created_at":"2025-10-14 20:50:29","extension":"png","order_by":36,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6546,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/4ac0521e6ec31a7fc7f2b927.png"},{"id":93529378,"identity":"f117dea2-49b0-4263-81f9-c6d448383c16","added_by":"auto","created_at":"2025-10-14 20:50:30","extension":"png","order_by":37,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8069,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/d58316eac36d2f515592dfe8.png"},{"id":93529391,"identity":"366bca85-e95d-46df-95d4-317257ab4862","added_by":"auto","created_at":"2025-10-14 20:50:30","extension":"xml","order_by":38,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":125280,"visible":true,"origin":"","legend":"","description":"","filename":"7579db25a921478d9246c25a7b17fac61structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/021a0093456eec155411e16f.xml"},{"id":93530589,"identity":"4240649c-491b-41dc-bb1a-702bcf0a51ac","added_by":"auto","created_at":"2025-10-14 20:58:30","extension":"html","order_by":39,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":141437,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1/50df05dd2bae20d55ae23595.html"},{"id":97330598,"identity":"bdfa60e3-fa82-4021-900c-0c1bbc3c8b20","added_by":"auto","created_at":"2025-12-03 09:09:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1172062,"visible":true,"origin":"","legend":"","description":"","filename":"AdaptiveSpectrum.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7585019/v1_covered_cdce9b04-0184-4953-9e89-136cd3dbd14e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Adaptive Spectrum Sensing and Management in Cognitive Radio Networks Using Federated Deep Reinforcement Learning","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":"Spectrum sensing, Cognitive radio networks, Federated deep reinforcement learning, DBN, LSTM","lastPublishedDoi":"10.21203/rs.3.rs-7585019/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7585019/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe dynamic and unexpected character of settings in wireless communication calls for sophisticated spectrum sensing techniques for cognitive radio networks. Building on the work of earlier ensemble machine learning approaches, this study presents a state-of-the-art framework for real-time spectrum management using federated deep reinforcement learning (FDRL). The combination of reinforcement learning's strategic decision-making process with Deep Belief Networks' (DBN) and Long Short-Term Memory's (LSTM) architectures is at the heart of this methodology. This approach, which operates inside a federated learning paradigm, gives user privacy and data locality, guaranteeing a reliable and private solution. Through processing signal vectors under different noise situations, the FDRL model repeatedly learns the best spectrum allocation strategies, improving its comprehension over time. This novel approach offers effective adaptability to the ever-changing wireless environment, improving network speed and spectrum utilization while protecting user privacy. Effectively separating idle from active channels, it continuously adjusts to variations in signal-to-noise ratios and user demands. This sophisticated technology is shown through thorough simulations to provide a significant improvement in both spectrum efficiency and user throughput. Because of its scalability and decentralization, it presents a viable answer to the changing wireless network environment, which is marked by an increasing need for autonomy and data-driven operations. This approach's proven ability to reduce interference and improve service quality indicates a major step forward for intelligent and autonomous spectrum sensing methods, which are critical in the age of ubiquitous wireless communication. The suggested FDRL-DBN-LSTM approach was implemented in Python and achieves an accuracy of 98.4%.\u003c/p\u003e","manuscriptTitle":"Adaptive Spectrum Sensing and Management in Cognitive Radio Networks Using Federated Deep Reinforcement Learning","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-14 20:50:24","doi":"10.21203/rs.3.rs-7585019/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":"2cb9e0ad-0995-446b-9ef5-ea2c02c09666","owner":[],"postedDate":"October 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-03T09:08:42+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-14 20:50:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7585019","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7585019","identity":"rs-7585019","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}