{"id":"https://openalex.org/W7161052802","doi":"https://doi.org/10.48550/arxiv.2605.11875","title":"Modulation Consistency-based Contrastive Learning for Self-Supervised Automatic Modulation Classification","display_name":"Modulation Consistency-based Contrastive Learning for Self-Supervised Automatic Modulation Classification","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7161052802","doi":"https://doi.org/10.48550/arxiv.2605.11875"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.11875","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11875","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.11875","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136019763","display_name":"Chenxu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Chenxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136072909","display_name":"Shuang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075007359","display_name":"Lirong Han","orcid":"https://orcid.org/0000-0002-8613-7037"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Lirong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136031065","display_name":"Xinyu Hu","orcid":"https://orcid.org/0000-0002-1254-4844"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Xinyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136018013","display_name":"Hanlin Mo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mo, Hanlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000801494","display_name":"Hantong Xing","orcid":"https://orcid.org/0000-0002-5316-6077"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Hantong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136032387","display_name":"Licheng Jiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiao, Licheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9886000156402588,"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":0.9886000156402588,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0026000000070780516,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0012000000569969416,"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/modulation","display_name":"Modulation (music)","score":0.6988000273704529},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.484499990940094},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4521999955177307},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.41359999775886536},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4115999937057495},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.39910000562667847},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.38760000467300415},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3815000057220459},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.375900000333786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7412999868392944},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.6988000273704529},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5248000025749207},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4629000127315521},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4521999955177307},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.41359999775886536},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.38760000467300415},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C11930861","wikidata":"https://www.wikidata.org/wiki/Q181417","display_name":"Frequency modulation","level":3,"score":0.36970001459121704},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34380000829696655},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.33169999718666077},{"id":"https://openalex.org/C2779627259","wikidata":"https://www.wikidata.org/wiki/Q779763","display_name":"Pretext","level":3,"score":0.31690001487731934},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.28060001134872437},{"id":"https://openalex.org/C207717533","wikidata":"https://www.wikidata.org/wiki/Q863505","display_name":"Binary offset carrier modulation","level":5,"score":0.26820001006126404},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.11875","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11875","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.11875","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11875","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning-based":[1],"AMC":[2,32],"methods":[3,33],"have":[4],"achieved":[5],"remarkable":[6],"performance,":[7],"but":[8],"their":[9],"practical":[10],"deployment":[11],"remains":[12],"constrained":[13],"by":[14],"the":[15,26,75,84,118,124,157],"high":[16],"cost":[17],"of":[18,74,117],"labeled":[19],"data.":[20],"Although":[21],"self-supervised":[22],"learning":[23],"(SSL)":[24],"reduces":[25],"reliance":[27],"on":[28,36,97,171],"labels,":[29],"existing":[30],"SSL-based":[31],"often":[34],"rely":[35],"task-agnostic":[37],"pretext":[38],"objectives":[39],"misaligned":[40],"with":[41,48],"modulation":[42,63,86,129,159],"classification,":[43],"leading":[44],"to":[45,122,126,142,152],"representations":[46],"entangled":[47],"nuisance":[49,133],"factors":[50],"such":[51],"as":[52,65],"symbol,":[53],"channel,":[54],"and":[55,149],"noise.":[56],"In":[57],"this":[58,98],"paper,":[59],"we":[60,100],"identify":[61],"intra-instance":[62],"consistency":[64],"a":[66,90,103,138],"task-aware":[67],"structural":[68],"prior,":[69,99],"whereby":[70],"different":[71,114],"temporal":[72,115,147],"segments":[73,116],"same":[76,85,119,158],"signal":[77,120,167],"may":[78],"differ":[79],"in":[80,182,188],"waveform":[81],"while":[82,131,161],"preserving":[83],"type,":[87],"thus":[88],"providing":[89],"principled":[91],"cue":[92],"for":[93],"task-aligned":[94],"self-supervision.":[95],"Based":[96],"propose":[101],"Mod-CL,":[102,143],"Modulation":[104],"consistency-based":[105],"Contrastive":[106],"Learning":[107],"framework":[108],"that":[109,175],"constructs":[110],"positive":[111],"pairs":[112],"from":[113],"instance,":[121],"encourage":[123],"model":[125],"learn":[127],"shared":[128],"information":[130],"suppressing":[132],"variations.":[134],"We":[135],"further":[136],"develop":[137],"contrastive":[139],"objective":[140],"tailored":[141],"which":[144],"jointly":[145],"exploits":[146],"segmentation":[148],"data":[150],"augmentation":[151],"pull":[153],"together":[154],"views":[155],"sharing":[156],"semantics":[160],"avoiding":[162],"supervisory":[163],"conflicts":[164],"within":[165],"each":[166],"instance.":[168],"Extensive":[169],"experiments":[170],"RadioML":[172],"datasets":[173],"show":[174],"Mod-CL":[176],"consistently":[177],"outperforms":[178],"strong":[179],"baselines,":[180],"especially":[181],"low-label":[183],"regimes,":[184],"achieving":[185],"substantial":[186],"improvements":[187],"linear":[189],"probing":[190],"accuracy.":[191]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-14T00:00:00"}
