{"id":"https://openalex.org/W7139000687","doi":"https://doi.org/10.1109/globecom59602.2025.11432661","title":"Improving Automatic Modulation Long-Tail Recognition with Class-balancing Diffusion Model","display_name":"Improving Automatic Modulation Long-Tail Recognition with Class-balancing Diffusion Model","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7139000687","doi":"https://doi.org/10.1109/globecom59602.2025.11432661"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11432661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","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/A5130106222","display_name":"Yu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yu Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129782368","display_name":"Xiaoran Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoran Shi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101941620","display_name":"Haoyue Tan","orcid":"https://orcid.org/0009-0000-4987-6909"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haoyue Tan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129867249","display_name":"Feng Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng Zhou","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5130106222"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.88153072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3280","last_page":"3286"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.996999979019165,"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":0.996999979019165,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.00019999999494757503,"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"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/robustness","display_name":"Robustness (evolution)","score":0.7296000123023987},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.5673999786376953},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5666999816894531},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5069000124931335},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.48240000009536743},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39340001344680786},{"id":"https://openalex.org/keywords/attenuation","display_name":"Attenuation","score":0.36959999799728394},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3659999966621399},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3637999892234802}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7361000180244446},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7296000123023987},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.5673999786376953},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5666999816894531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5198000073432922},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.48240000009536743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4189000129699707},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39340001344680786},{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3659999966621399},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3637999892234802},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36010000109672546},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C11930861","wikidata":"https://www.wikidata.org/wiki/Q181417","display_name":"Frequency modulation","level":3,"score":0.32260000705718994},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.30230000615119934},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2913999855518341},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C101765175","wikidata":"https://www.wikidata.org/wiki/Q577764","display_name":"Communications system","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2540999948978424},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11432661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","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":14,"referenced_works":["https://openalex.org/W2741230443","https://openalex.org/W2963809753","https://openalex.org/W2995727660","https://openalex.org/W3032977069","https://openalex.org/W3193052805","https://openalex.org/W4205172454","https://openalex.org/W4226117432","https://openalex.org/W4285214623","https://openalex.org/W4391742924","https://openalex.org/W4392153330","https://openalex.org/W4399767281","https://openalex.org/W4400277774","https://openalex.org/W4403125548","https://openalex.org/W4408324873"],"related_works":[],"abstract_inverted_index":{"Automatic":[0],"modulation":[1,43,102],"recognition":[2,153],"(AMR)":[3],"is":[4],"critical":[5],"in":[6,152,171],"modern":[7],"wireless":[8,173],"communication":[9,174],"systems":[10],"and":[11,47,80,142,166],"cognitive":[12],"radio":[13],"applications.":[14],"Deep":[15],"learning":[16],"(DL)":[17],"methods":[18],"have":[19],"become":[20],"main-stream":[21],"for":[22,41,100],"AMR,":[23],"achieving":[24],"remarkable":[25],"performance":[26],"on":[27,68,140],"balanced":[28],"datasets.":[29],"However,":[30],"practical":[31],"scenarios":[32],"commonly":[33],"exhibit":[34],"long-tailed":[35,101,156],"distributions,":[36],"where":[37],"abundant":[38],"samples":[39,132],"exist":[40],"head":[42,62],"types":[44,49],"but":[45],"middle":[46],"tail":[48,69,130],"suffer":[50],"from":[51],"severe":[52],"scarcity.":[53],"Such":[54],"imbalance":[55,147],"biases":[56],"standard":[57],"DL":[58],"models":[59],"towards":[60],"the":[61,121],"classes,":[63],"significantly":[64],"compromising":[65],"their":[66],"effectiveness":[67],"classes.":[70],"Current":[71],"signal":[72],"balance":[73],"strategies":[74],"are":[75],"limited":[76],"by":[77],"domain-specific":[78],"knowledge":[79],"insufficient":[81],"sample":[82,135],"diversity.":[83,136],"To":[84],"address":[85],"these":[86],"challenges,":[87],"this":[88],"paper":[89],"proposes":[90],"DiffuMLR,":[91],"a":[92,107,112],"novel":[93],"class-dependent":[94],"label":[95,108,118],"information":[96],"attenuation":[97],"diffusion":[98,113],"model":[99,169],"recognition.":[103],"Specifically,":[104],"we":[105],"propose":[106],"decay":[109],"mechanism":[110],"within":[111],"probabilistic":[114],"model,":[115],"dynamically":[116],"adjusting":[117],"contributions":[119],"during":[120],"reverse":[122],"denoising":[123],"process.":[124],"DiffuMLR":[125,158],"ensures":[126],"semantic":[127],"invariance":[128],"of":[129],"class":[131],"while":[133],"enhancing":[134],"Extensive":[137],"experiments":[138],"conducted":[139],"real-world":[141],"public":[143],"datasets":[144],"with":[145,162],"varying":[146],"factors":[148],"demonstrate":[149],"significant":[150],"improvements":[151],"accuracy":[154],"under":[155],"conditions.":[157],"can":[159],"seamlessly":[160],"integrate":[161],"existing":[163],"AMR":[164,168],"architectures":[165],"enhance":[167],"robustness":[170],"realistic":[172],"scenarios.":[175]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}
