{"id":"https://openalex.org/W3038692183","doi":"https://doi.org/10.1109/vtc2020-spring48590.2020.9129576","title":"Modulation Classification Method based on Deep Learning under Non-Gaussian Noise","display_name":"Modulation Classification Method based on Deep Learning under Non-Gaussian Noise","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3038692183","doi":"https://doi.org/10.1109/vtc2020-spring48590.2020.9129576","mag":"3038692183"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2020-spring48590.2020.9129576","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2020-spring48590.2020.9129576","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)","raw_type":"proceedings-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/A5055151215","display_name":"Minghuan Ma","orcid":"https://orcid.org/0000-0001-5168-7189"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Minghuan Ma","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University, Harbin, P.R.China"],"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, P.R.China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100363805","display_name":"Zhigang Li","orcid":"https://orcid.org/0000-0002-6230-6959"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Li","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University, Harbin, P.R.China"],"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, P.R.China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100778980","display_name":"Yun Lin","orcid":"https://orcid.org/0000-0002-4002-1282"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Lin","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University, Harbin, P.R.China"],"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, P.R.China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333466","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-3919-8056"},"institutions":[{"id":"https://openalex.org/I39815113","display_name":"Georgia Southern University","ror":"https://ror.org/04agmb972","country_code":"US","type":"education","lineage":["https://openalex.org/I39815113"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Department of Information Technology, Georgia Southern University, Georgia, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Georgia Southern University, Georgia, U.S.A","institution_ids":["https://openalex.org/I39815113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100350760","display_name":"Sen Wang","orcid":"https://orcid.org/0000-0003-1537-8834"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Wang","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University, Harbin, P.R.China"],"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, P.R.China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5055151215"],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":null,"apc_paid":null,"fwci":1.3716,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.85253409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9016000032424927,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7146714329719543},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6805680990219116},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.624952495098114},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.6141244173049927},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5783279538154602},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5750005841255188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5426474213600159},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5246061086654663},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5007472038269043},{"id":"https://openalex.org/keywords/quadrature-amplitude-modulation","display_name":"Quadrature amplitude modulation","score":0.44191643595695496},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.4359019994735718},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36638230085372925},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3309621810913086},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2853698134422302},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.25466644763946533},{"id":"https://openalex.org/keywords/bit-error-rate","display_name":"Bit error rate","score":0.19438034296035767},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.08837208151817322}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7146714329719543},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6805680990219116},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.624952495098114},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.6141244173049927},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5783279538154602},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5750005841255188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5426474213600159},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5246061086654663},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5007472038269043},{"id":"https://openalex.org/C32409245","wikidata":"https://www.wikidata.org/wiki/Q749753","display_name":"Quadrature amplitude modulation","level":4,"score":0.44191643595695496},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.4359019994735718},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36638230085372925},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3309621810913086},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2853698134422302},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.25466644763946533},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.19438034296035767},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.08837208151817322},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2020-spring48590.2020.9129576","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2020-spring48590.2020.9129576","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)","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":15,"referenced_works":["https://openalex.org/W1972973610","https://openalex.org/W2548159479","https://openalex.org/W2734408173","https://openalex.org/W2737648313","https://openalex.org/W2770057541","https://openalex.org/W2773170971","https://openalex.org/W2790452209","https://openalex.org/W2884089434","https://openalex.org/W2892154397","https://openalex.org/W2899399724","https://openalex.org/W2908997014","https://openalex.org/W2916238263","https://openalex.org/W2943652919","https://openalex.org/W2944891925","https://openalex.org/W6757355660"],"related_works":["https://openalex.org/W2122253935","https://openalex.org/W4247508912","https://openalex.org/W1974392290","https://openalex.org/W2979776991","https://openalex.org/W3043454527","https://openalex.org/W2577885878","https://openalex.org/W3081379232","https://openalex.org/W2955217210","https://openalex.org/W3103566292","https://openalex.org/W1607924090"],"abstract_inverted_index":{"The":[0,104,137],"arrival":[1],"of":[2,8,11,23,143,162],"5G":[3],"has":[4,41],"accelerated":[5],"the":[6,9,46,59,76,110,118,134,144,148,159],"development":[7],"Internet":[10],"things":[12],"and":[13,50,116,123],"vehicular":[14],"technology,":[15],"which":[16,126],"often":[17],"need":[18],"to":[19,44,65,129,158],"transmit":[20],"large":[21],"amounts":[22],"data":[24],"through":[25],"wireless":[26,35,86],"networks.":[27],"Modulation":[28],"classification":[29,48,53,68,93],"plays":[30],"an":[31],"important":[32],"role":[33],"in":[34,70,84,95,113,133],"communication.":[36,87],"Recent":[37],"years,":[38],"deep":[39,63],"learning":[40,64],"been":[42],"applied":[43],"solve":[45,66],"modulation":[47,67,92,119],"problem":[49],"achieved":[51],"good":[52],"results.":[54],"At":[55,147],"present,":[56],"almost":[57],"all":[58],"papers":[60],"that":[61,141,153],"use":[62],"are":[69,127,131],"Gaussian":[71],"White":[72],"noise":[73,83,115],"environment.":[74],"However,":[75],"error":[77],"source":[78],"mainly":[79],"comes":[80],"from":[81],"non-Gaussian":[82,96,114],"practical":[85],"In":[88],"this":[89,154],"paper,":[90],"a":[91],"method":[94,155],"environment":[97],"based":[98],"on":[99],"Deep":[100],"Learning":[101],"is":[102,156],"proposed.":[103],"proposed":[105,145],"algorithm":[106],"can":[107],"effectively":[108],"suppress":[109],"sharp":[111],"pulse":[112],"improve":[117],"recognition":[120],"accuracy.":[121],"MPSK":[122],"MQAM":[124],"signals":[125],"difficult":[128],"distinguish":[130],"adopted":[132],"simulation":[135,138],"experiment.":[136],"results":[139],"show":[140,152],"validity":[142],"method.":[146],"same":[149],"time,":[150],"experiments":[151],"robust":[157],"characteristic":[160],"exponent":[161],"noise.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}