{"id":"https://openalex.org/W3091910947","doi":"https://doi.org/10.1109/pimrc48278.2020.9217305","title":"Automatic Modulation Classification Using Multi-Scale Convolutional Neural Network","display_name":"Automatic Modulation Classification Using Multi-Scale Convolutional Neural Network","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3091910947","doi":"https://doi.org/10.1109/pimrc48278.2020.9217305","mag":"3091910947"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc48278.2020.9217305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc48278.2020.9217305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications","raw_type":"proceedings-article"},"type":"conference-paper","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/A5055021669","display_name":"Hongtai Chen","orcid":"https://orcid.org/0000-0002-5035-9236"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongtai Chen","raw_affiliation_strings":["Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100675165","display_name":"Li Guo","orcid":"https://orcid.org/0000-0002-9723-3294"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Guo","raw_affiliation_strings":["Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048708984","display_name":"Chao Dong","orcid":"https://orcid.org/0000-0002-4922-7762"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Dong","raw_affiliation_strings":["Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085073312","display_name":"Fuze Cong","orcid":"https://orcid.org/0000-0002-0947-2392"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuze Cong","raw_affiliation_strings":["Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056349361","display_name":"Xidong Mu","orcid":"https://orcid.org/0000-0001-8351-360X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xidong Mu","raw_affiliation_strings":["Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Beijing University of Posts and Telecommunications Key Lab of Universal Wireless Communications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":1.035,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.81005275,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":1.0,"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":1.0,"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"}},{"id":"https://openalex.org/T10207","display_name":"Advanced biosensing and bioanalysis techniques","score":0.9645000100135803,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9031000137329102,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7393749952316284},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7049027681350708},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6925140619277954},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6700016856193542},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.653715193271637},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5981168746948242},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5916564464569092},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.4860680401325226},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4780314862728119},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.46820905804634094},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43733227252960205},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.25441670417785645}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7393749952316284},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7049027681350708},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6925140619277954},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6700016856193542},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.653715193271637},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5981168746948242},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5916564464569092},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.4860680401325226},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4780314862728119},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.46820905804634094},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43733227252960205},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25441670417785645},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/pimrc48278.2020.9217305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc48278.2020.9217305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2005956500","https://openalex.org/W2104885797","https://openalex.org/W2120019163","https://openalex.org/W2147576921","https://openalex.org/W2170778725","https://openalex.org/W2272847350","https://openalex.org/W2603396821","https://openalex.org/W2734908518","https://openalex.org/W2741230443","https://openalex.org/W2753161394","https://openalex.org/W2773170971","https://openalex.org/W2803445619","https://openalex.org/W2887987067","https://openalex.org/W2892154397","https://openalex.org/W2912136746","https://openalex.org/W2912386632","https://openalex.org/W2914940294","https://openalex.org/W2915108913","https://openalex.org/W2916798096","https://openalex.org/W2921683268","https://openalex.org/W2946774101","https://openalex.org/W2961742849","https://openalex.org/W2963577893","https://openalex.org/W2966573466","https://openalex.org/W2999595914","https://openalex.org/W3000943722","https://openalex.org/W3005510567","https://openalex.org/W3008364176","https://openalex.org/W3104028856","https://openalex.org/W3134059753","https://openalex.org/W4288365549","https://openalex.org/W6754041223","https://openalex.org/W6762113363"],"related_works":["https://openalex.org/W2397288865","https://openalex.org/W2368524271","https://openalex.org/W4247116873","https://openalex.org/W2576709312","https://openalex.org/W2023657818","https://openalex.org/W2392797073","https://openalex.org/W2384907669","https://openalex.org/W2095030957","https://openalex.org/W2066827917","https://openalex.org/W2884201223"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,185],"multi-scale":[4,54,67,75,93],"convolutional":[5],"neural":[6],"network-based":[7],"(MSN)":[8],"method":[9],"is":[10,195],"proposed":[11,125,176],"for":[12,138],"robust":[13,198],"automatic":[14],"modulation":[15,30,111,141,156],"classification":[16,82,128,132,191],"(AMC).":[17],"The":[18],"classifier":[19,181],"directly":[20],"utilizes":[21],"in-phase":[22],"and":[23,85],"quadrature":[24],"(I/Q)":[25],"samples":[26],"to":[27,52,58,79,88,173],"identify":[28],"the":[29,41,45,81,86,106,115,119,144,155,162,174,196],"type":[31],"of":[32,61,99,118,130,158,165,190],"received":[33,159],"signal":[34],"without":[35],"any":[36],"data":[37],"preprocessing,":[38],"thereby":[39],"reducing":[40],"computational":[42,63],"complexity.":[43,64],"Further,":[44],"network":[46],"architecture":[47],"employs":[48],"one-dimensional":[49],"convolution":[50],"(Conv1D)":[51],"extract":[53],"feature":[55,68],"maps":[56,69],"due":[57],"its":[59],"merits":[60],"low":[62],"Then":[65],"these":[66],"are":[70],"merged":[71],"together":[72],"by":[73,110],"repeated":[74],"fusions,":[76],"in":[77,177,188,199],"order":[78],"improve":[80],"accuracy":[83,133,163],"performance":[84,187],"robustness":[87],"varying":[89,169,200],"SNR":[90,136,170,201],"environment.":[91,202],"Repeated":[92],"fusions":[94],"can":[95,104,153],"make":[96],"better":[97,186],"use":[98],"amplitude-phase":[100],"information":[101],"because":[102],"it":[103],"learn":[105],"local":[107],"changes":[108],"brought":[109],"as":[112,114],"well":[113],"timing":[116],"characteristics":[117],"samples.":[120],"Simulation":[121],"results":[122],"show":[123],"that":[124],"MSN":[126,151],"achieves":[127],"rate":[129],"97.38%":[131],"at":[134],"high":[135],"regimes":[137],"24":[139],"different":[140],"types":[142,157],"on":[143],"public":[145],"well-known":[146],"over-the-air":[147],"(OTA)":[148],"dataset.":[149],"Moreover,":[150],"still":[152],"recognize":[154],"signals":[160],"with":[161],"rates":[164],"about":[166],"95%":[167],"under":[168],"scenarios.":[171],"Compared":[172],"methods":[175],"other":[178],"papers,":[179],"our":[180],"not":[182],"only":[183],"shows":[184],"terms":[189],"accuracy,":[192],"but":[193],"also":[194],"most":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
