Lightweight signal recognition based on hybrid model in wireless networks

Lightweight signal recognition based on hybrid model in wireless 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 Research Article Lightweight signal recognition based on hybrid model in wireless networks Rui Gao, Lan Guo, Mingjun Tang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4304385/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Aug, 2024 Read the published version in Telecommunication Systems → Version 1 posted 11 You are reading this latest preprint version Abstract As a key technology in wireless networks, signal recognition is widely used in various military and civilian fields. By correctly recognizing the modulation scheme of the received unknown signal, the performance of the communication system can be improved. With the comprehensive digitization and intelligence of the world, the rapid development of wireless communication puts forward higher requirements for signal recognition: 1) Accurate and efficient recognition of various modulation modes and 2) Lightweight recognition of intelligent hardware. Therefore, through in-depth study of hybrid model and lightweight modulation recognition, this paper first designs a hybrid signal recognition model based on convolutional neural network and gating recursive unit (CnGr). By combining the spatial module with the temporal module, the multi-dimensional extraction of the original signal is promoted and the recognition accuracy is effectively improved. Further, a lightweight signal recognition method is given by combining pruning and depthwise separable convolution. The network can be reduced effectively on the premise of ensuring the recognition accuracy, which facilitates the deployment and implementation on edge devices. Extensive experiments demonstrate that the proposed method can effectively improve the recognition accuracy, and reduce the model significantly without reducing the accuracy. Signal recognition wireless networks deep learning hybrid neural network Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Aug, 2024 Read the published version in Telecommunication Systems → Version 1 posted Editorial decision: Revision requested 02 Jun, 2024 Reviews received at journal 29 May, 2024 Reviews received at journal 25 May, 2024 Reviews received at journal 22 May, 2024 Reviewers agreed at journal 01 May, 2024 Reviewers agreed at journal 28 Apr, 2024 Reviewers agreed at journal 28 Apr, 2024 Reviewers invited by journal 28 Apr, 2024 Submission checks completed at journal 27 Apr, 2024 Editor assigned by journal 27 Apr, 2024 First submitted to journal 22 Apr, 2024 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-4304385","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":297768710,"identity":"84a4399a-c700-4a5b-a0dc-0bd414759f29","order_by":0,"name":"Rui Gao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYNACAxsIzUOCljSStTAcJkGLvPvhY595Cs4nzp+RwPjgbRuDvDkhLYZn0pJn8xjcTmyckcBsOLeNwXBnAyEtDTnGzCAtzRIJbNK8bQwJBgcIael/A9JyLrFNIoH9N1Fa5CXAthxI7AHawkyUFgOJZ8mMcwySjWfwPGyWnHNOwnADQVv6kw8zvPljJzu/PfnghzdlNvKEbYEqcGxgYGwA0hIE1INsaYDQ9oSVjoJRMApGwYgFAARcOkqVKGVEAAAAAElFTkSuQmCC","orcid":"","institution":"Yangzhou University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Gao","suffix":""},{"id":297768714,"identity":"832bebc6-1fad-4231-8093-4d7333a54e8d","order_by":1,"name":"Lan Guo","email":"","orcid":"","institution":"Yangzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lan","middleName":"","lastName":"Guo","suffix":""},{"id":297768722,"identity":"d47875b0-6b07-4bec-8544-885b16274a3e","order_by":2,"name":"Mingjun Tang","email":"","orcid":"","institution":"Yangzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mingjun","middleName":"","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2024-04-22 08:38:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4304385/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4304385/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11235-024-01204-8","type":"published","date":"2024-08-06T15:57:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62298432,"identity":"08949c60-ceee-47e0-a9e7-5c8626df5eb7","added_by":"auto","created_at":"2024-08-12 16:13:16","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2168260,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4304385/v1_covered_5cf277c1-d4ad-4226-b9bc-81acf7568f21.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Lightweight signal recognition based on hybrid model in wireless networks","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"telecommunication-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tels","sideBox":"Learn more about [Telecommunication Systems](https://www.springer.com/journal/11235)","snPcode":"11235","submissionUrl":"https://submission.nature.com/new-submission/11235/3","title":"Telecommunication Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Signal recognition, wireless networks, deep learning, hybrid neural network","lastPublishedDoi":"10.21203/rs.3.rs-4304385/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4304385/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"As a key technology in wireless networks, signal recognition is widely used in various military and civilian fields. By correctly recognizing the modulation scheme of the received unknown signal, the performance of the communication system can be improved. With the comprehensive digitization and intelligence of the world, the rapid development of wireless communication puts forward higher requirements for signal recognition: 1) Accurate and efficient recognition of various modulation modes and 2) Lightweight recognition of intelligent hardware. Therefore, through in-depth study of hybrid model and lightweight modulation recognition, this paper first designs a hybrid signal recognition model based on convolutional neural network and gating recursive unit (CnGr). By combining the spatial module with the temporal module, the multi-dimensional extraction of the original signal is promoted and the recognition accuracy is effectively improved. Further, a lightweight signal recognition method is given by combining pruning and depthwise separable convolution. The network can be reduced effectively on the premise of ensuring the recognition accuracy, which facilitates the deployment and implementation on edge devices. Extensive experiments demonstrate that the proposed method can effectively improve the recognition accuracy, and reduce the model significantly without reducing the accuracy.","manuscriptTitle":"Lightweight signal recognition based on hybrid model in wireless networks","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-03 20:17:02","doi":"10.21203/rs.3.rs-4304385/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-02T10:10:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-29T07:04:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-25T12:42:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-23T02:59:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"252569966460200509128563536517273125377","date":"2024-05-01T09:36:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"114608607288659960689035790987609031447","date":"2024-04-29T03:11:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265477726827454077265073406664097460790","date":"2024-04-29T00:41:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-28T23:47:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-27T09:12:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-27T09:12:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Telecommunication Systems","date":"2024-04-22T08:26:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"telecommunication-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tels","sideBox":"Learn more about [Telecommunication Systems](https://www.springer.com/journal/11235)","snPcode":"11235","submissionUrl":"https://submission.nature.com/new-submission/11235/3","title":"Telecommunication Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"dcd28521-196b-4b45-b77b-c42edfea72f2","owner":[],"postedDate":"May 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-12T16:03:56+00:00","versionOfRecord":{"articleIdentity":"rs-4304385","link":"https://doi.org/10.1007/s11235-024-01204-8","journal":{"identity":"telecommunication-systems","isVorOnly":false,"title":"Telecommunication Systems"},"publishedOn":"2024-08-06 15:57:44","publishedOnDateReadable":"August 6th, 2024"},"versionCreatedAt":"2024-05-03 20:17:02","video":"","vorDoi":"10.1007/s11235-024-01204-8","vorDoiUrl":"https://doi.org/10.1007/s11235-024-01204-8","workflowStages":[]},"version":"v1","identity":"rs-4304385","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4304385","identity":"rs-4304385","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}