{"id":"https://openalex.org/W4405933974","doi":"https://doi.org/10.1109/jiot.2024.3524380","title":"Hybrid-Driven Model Fusing Deep Learning and Knowledge for Automatic Modulation Recognition","display_name":"Hybrid-Driven Model Fusing Deep Learning and Knowledge for Automatic Modulation Recognition","publication_year":2024,"publication_date":"2024-12-31","ids":{"openalex":"https://openalex.org/W4405933974","doi":"https://doi.org/10.1109/jiot.2024.3524380"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3524380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3524380","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100752983","display_name":"Bin Wang","orcid":"https://orcid.org/0000-0002-2940-3001"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bin Wang","raw_affiliation_strings":["School of Communication Engineering, Xi’an University of Science and Technology, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-2940-3001","affiliations":[{"raw_affiliation_string":"School of Communication Engineering, Xi’an University of Science and Technology, Xi’an, China","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021180689","display_name":"Zhuang Yuan","orcid":"https://orcid.org/0000-0003-1937-278X"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuang Yuan","raw_affiliation_strings":["School of Communication Engineering, Xi’an University of Science and Technology, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-1937-278X","affiliations":[{"raw_affiliation_string":"School of Communication Engineering, Xi’an University of Science and Technology, Xi’an, China","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025437779","display_name":"Aiping Li","orcid":"https://orcid.org/0009-0001-2378-5352"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aiping Li","raw_affiliation_strings":["School of Communication Engineering, Xi’an University of Science and Technology, Xi’an, China"],"raw_orcid":"https://orcid.org/0009-0001-2378-5352","affiliations":[{"raw_affiliation_string":"School of Communication Engineering, Xi’an University of Science and Technology, Xi’an, China","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102024260","display_name":"Jun Lu","orcid":"https://orcid.org/0009-0003-0652-6812"},"institutions":[{"id":"https://openalex.org/I4210092870","display_name":"Jiaxing University","ror":"https://ror.org/00j2a7k55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092870"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Lu","raw_affiliation_strings":["Key Laboratory of Multimodal Sensing and Intelligent Systems of Zhejiang Province, Jiaxing University, Jiaxing, China"],"raw_orcid":"https://orcid.org/0009-0003-0652-6812","affiliations":[{"raw_affiliation_string":"Key Laboratory of Multimodal Sensing and Intelligent Systems of Zhejiang Province, Jiaxing University, Jiaxing, China","institution_ids":["https://openalex.org/I4210092870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102744584","display_name":"Xianchao Zhang","orcid":"https://orcid.org/0000-0001-8925-8371"},"institutions":[{"id":"https://openalex.org/I4210092870","display_name":"Jiaxing University","ror":"https://ror.org/00j2a7k55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092870"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianchao Zhang","raw_affiliation_strings":["Key Laboratory of Multimodal Sensing and Intelligent Systems of Zhejiang Province, Jiaxing University, Jiaxing, China"],"raw_orcid":"https://orcid.org/0000-0001-8925-8371","affiliations":[{"raw_affiliation_string":"Key Laboratory of Multimodal Sensing and Intelligent Systems of Zhejiang Province, Jiaxing University, Jiaxing, China","institution_ids":["https://openalex.org/I4210092870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100752983"],"corresponding_institution_ids":["https://openalex.org/I110440473"],"apc_list":null,"apc_paid":null,"fwci":0.6623,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77059827,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"12","issue":"10","first_page":"13934","last_page":"13945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7894842624664307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5330544710159302},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5197420120239258},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.4224676489830017},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.4210675060749054},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33540889620780945},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.16300570964813232}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7894842624664307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5330544710159302},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5197420120239258},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.4224676489830017},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.4210675060749054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33540889620780945},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.16300570964813232},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2024.3524380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3524380","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3579604313","display_name":null,"funder_award_id":"62471385","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8566436617","display_name":null,"funder_award_id":"2022YFB4401904","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8965635672","display_name":null,"funder_award_id":"U19B2015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1986510668","https://openalex.org/W2130014182","https://openalex.org/W2147735901","https://openalex.org/W2147893740","https://openalex.org/W2272847350","https://openalex.org/W2560119283","https://openalex.org/W2603396821","https://openalex.org/W2724492314","https://openalex.org/W2741230443","https://openalex.org/W2892154397","https://openalex.org/W2916820451","https://openalex.org/W2973449430","https://openalex.org/W2986739745","https://openalex.org/W3000943722","https://openalex.org/W3003494250","https://openalex.org/W3032977069","https://openalex.org/W3095073866","https://openalex.org/W3115053547","https://openalex.org/W3126877825","https://openalex.org/W3193052805","https://openalex.org/W4205590867","https://openalex.org/W4210572636","https://openalex.org/W4226117432","https://openalex.org/W4285407052","https://openalex.org/W4285741054","https://openalex.org/W4320018370","https://openalex.org/W4321483861","https://openalex.org/W4324290967","https://openalex.org/W4365801635","https://openalex.org/W4379116642","https://openalex.org/W4382677708","https://openalex.org/W4386078135","https://openalex.org/W4387145975","https://openalex.org/W4387623697","https://openalex.org/W4390284853","https://openalex.org/W4390285034","https://openalex.org/W4390806957","https://openalex.org/W4391235420","https://openalex.org/W4391407019","https://openalex.org/W4396941254","https://openalex.org/W4399310837","https://openalex.org/W4399619729","https://openalex.org/W4403279499"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W3086377361"],"abstract_inverted_index":{"Automatic":[0],"modulation":[1,63],"recognition":[2,15,64,139],"plays":[3],"a":[4,26,110],"crucial":[5],"role":[6],"in":[7,39,65,84,100,141],"the":[8,46,60,94,101],"domain":[9,103],"of":[10,29,49,62,77,97],"electromagnetic":[11,67,86],"situational":[12],"awareness.":[13],"Early":[14],"methods":[16,71,127],"predominantly":[17],"relied":[18],"on":[19,74,133,146],"expert":[20,98,134],"experience":[21,33],"and":[22,32,36,81,104,149,159],"prior":[23],"knowledge,":[24,135],"demanding":[25],"high":[27],"level":[28],"professional":[30],"background":[31],"from":[34],"practitioners,":[35],"usually":[37],"underperformed":[38],"complex":[40,66],"signal":[41,118],"environments.":[42,68],"In":[43],"recent":[44],"years,":[45],"continual":[47],"development":[48],"deep":[50,122],"learning":[51],"(DL)":[52],"technologies":[53],"has":[54],"introduced":[55],"solution":[56],"ideas":[57],"to":[58,137],"address":[59],"challenge":[61],"However,":[69],"DL":[70],"heavily":[72],"depend":[73],"large":[75],"volumes":[76],"high-quality":[78],"labeled":[79],"data":[80],"face":[82],"challenges":[83],"real":[85,150],"environments":[87],"with":[88,128],"limited":[89],"samples.":[90],"To":[91],"fully":[92],"leverage":[93],"respective":[95],"strengths":[96],"knowledge":[99],"radio":[102,117],"data-driven":[105,126],"approaches,":[106],"this":[107],"article":[108],"proposes":[109],"hybrid-driven":[111],"neural":[112],"network":[113],"(HDNet)":[114],"framework":[115],"for":[116],"recognition.":[119],"HDNet":[120,155],"integrates":[121],"features":[123,130],"extracted":[124,131],"through":[125],"manual":[129],"based":[132],"aiming":[136],"enhance":[138],"performance":[140],"few-shot":[142],"scenarios.":[143],"Experimental":[144],"results":[145],"both":[147],"simulated":[148],"measured":[151],"datasets":[152],"demonstrate":[153],"that":[154],"achieves":[156],"high-recognition":[157],"accuracy":[158],"robustness.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}