{"id":"https://openalex.org/W4393078957","doi":"https://doi.org/10.1109/lcomm.2024.3380623","title":"A Transformer and Convolution-Based Learning Framework for Automatic Modulation Classification","display_name":"A Transformer and Convolution-Based Learning Framework for Automatic Modulation Classification","publication_year":2024,"publication_date":"2024-03-22","ids":{"openalex":"https://openalex.org/W4393078957","doi":"https://doi.org/10.1109/lcomm.2024.3380623"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2024.3380623","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2024.3380623","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","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 Communications Letters","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/A5031713467","display_name":"Wenxuan Ma","orcid":"https://orcid.org/0000-0003-0257-6073"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenxuan Ma","raw_affiliation_strings":["School of Physics and Electronic Information, Yantai University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Information, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010365496","display_name":"Zhuoran Cai","orcid":"https://orcid.org/0000-0001-9793-8684"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuoran Cai","raw_affiliation_strings":["School of Physics and Electronic Information, Yantai University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Information, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100443590","display_name":"Chuan Wang","orcid":"https://orcid.org/0000-0002-0466-3165"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Wang","raw_affiliation_strings":["School of Physics and Electronic Information, Yantai University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Information, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5031713467"],"corresponding_institution_ids":["https://openalex.org/I18452120"],"apc_list":null,"apc_paid":null,"fwci":9.2143,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.98234092,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"28","issue":"6","first_page":"1392","last_page":"1396"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9894000291824341,"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":0.9894000291824341,"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":0.7219496369361877},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5142635703086853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45310255885124207},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.4284096956253052},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40800562500953674},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34464505314826965},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.34294065833091736},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.15378358960151672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7219496369361877},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5142635703086853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45310255885124207},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.4284096956253052},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40800562500953674},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34464505314826965},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.34294065833091736},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.15378358960151672},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2024.3380623","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2024.3380623","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","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 Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1600744878","https://openalex.org/W1985690171","https://openalex.org/W2002643600","https://openalex.org/W2130014182","https://openalex.org/W2603396821","https://openalex.org/W2741230443","https://openalex.org/W2963809753","https://openalex.org/W2983220838","https://openalex.org/W3000943722","https://openalex.org/W3032977069","https://openalex.org/W3104028856","https://openalex.org/W3104581735","https://openalex.org/W3126877825","https://openalex.org/W3179869055","https://openalex.org/W3193052805","https://openalex.org/W3193513114","https://openalex.org/W4226224676","https://openalex.org/W4285222140","https://openalex.org/W4375868987","https://openalex.org/W6766904570","https://openalex.org/W6917408469"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2182785089","https://openalex.org/W4387838477","https://openalex.org/W2067193074","https://openalex.org/W3107426390","https://openalex.org/W4312178642","https://openalex.org/W2375093801","https://openalex.org/W1534368937","https://openalex.org/W4224009465","https://openalex.org/W4312624109"],"abstract_inverted_index":{"Automatic":[0],"modulation":[1],"classification":[2,8,94],"(AMC)":[3],"is":[4,11,68],"a":[5,37,69,77],"typical":[6],"pattern":[7],"task":[9],"that":[10,87],"an":[12],"intermediate":[13],"process":[14],"between":[15],"signal":[16],"detection":[17],"and":[18,74],"demodulation.":[19],"Deep":[20],"learning":[21],"methods":[22],"used":[23],"in":[24,80],"AMC,":[25],"such":[26],"as":[27],"convolutional":[28],"neural":[29],"network":[30,42],"(CNN)":[31],"have":[32],"their":[33],"shortcomings.":[34],"We":[35],"propose":[36],"new":[38],"parallel":[39,70],"CNN":[40,62,73],"transformer":[41,51],"(PCTNet),":[43],"which":[44],"not":[45],"only":[46],"possesses":[47],"the":[48,59,81],"advantages":[49,60],"of":[50,61,72],"to":[52,63],"capture":[53],"long-range":[54],"dependencies,":[55],"but":[56],"also":[57],"utilizes":[58],"extract":[64],"local":[65],"information.":[66],"PCTNet":[67,90],"design":[71],"transformer,":[75],"with":[76],"delivery":[78],"mechanism":[79],"middle.":[82],"Extensive":[83],"simulation":[84],"results":[85],"show":[86],"our":[88],"proposed":[89],"can":[91],"achieve":[92],"superior":[93],"performance":[95],"than":[96],"traditional":[97],"deep":[98],"models.":[99]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
