{"id":"https://openalex.org/W4402159233","doi":"https://doi.org/10.1109/icc51166.2024.10622929","title":"Adaptive Denoising With Efficient Channel Attention for Automatic Modulation Recognition","display_name":"Adaptive Denoising With Efficient Channel Attention for Automatic Modulation Recognition","publication_year":2024,"publication_date":"2024-06-09","ids":{"openalex":"https://openalex.org/W4402159233","doi":"https://doi.org/10.1109/icc51166.2024.10622929"},"language":"en","primary_location":{"id":"doi:10.1109/icc51166.2024.10622929","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc51166.2024.10622929","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2024 - IEEE International Conference on Communications","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/A5058268359","display_name":"Hao Zhu","orcid":"https://orcid.org/0000-0003-4411-0933"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Zhu","raw_affiliation_strings":["College of Electronics and Information Engineering, Shenzhen University"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069876128","display_name":"Yuan Ma","orcid":"https://orcid.org/0000-0003-0648-8492"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Ma","raw_affiliation_strings":["College of Electronics and Information Engineering, Shenzhen University"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100635710","display_name":"Xingjian Zhang","orcid":"https://orcid.org/0000-0001-5423-963X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingjian Zhang","raw_affiliation_strings":["College of Electronics and Information Engineering, Harbin Institute of Technology (Shenzhen)"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Harbin Institute of Technology (Shenzhen)","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058892726","display_name":"Caiyong Hao","orcid":"https://orcid.org/0000-0001-7003-7501"},"institutions":[{"id":"https://openalex.org/I4210143635","display_name":"State Radio Regulation Of China","ror":"https://ror.org/041100z65","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210143635","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caiyong Hao","raw_affiliation_strings":["Shenzhen Station, State Radio Monitoring Center,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Station, State Radio Monitoring Center,Shenzhen,China","institution_ids":["https://openalex.org/I4210143635"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058268359"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.7274,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.75854558,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2113","last_page":"2118"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12946","display_name":"Fractal and DNA sequence analysis","score":0.9772999882698059,"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":0.6861875057220459},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5885626077651978},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.5539214611053467},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5076388120651245},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.48937124013900757},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4499378204345703},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4170122742652893},{"id":"https://openalex.org/keywords/selective-attention","display_name":"Selective attention","score":0.41611573100090027},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.18724703788757324},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12766143679618835},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.0864005982875824},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.06346374750137329},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.05452698469161987}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6861875057220459},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5885626077651978},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.5539214611053467},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5076388120651245},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.48937124013900757},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4499378204345703},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4170122742652893},{"id":"https://openalex.org/C2989146674","wikidata":"https://www.wikidata.org/wiki/Q4818236","display_name":"Selective attention","level":3,"score":0.41611573100090027},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.18724703788757324},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12766143679618835},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.0864005982875824},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.06346374750137329},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.05452698469161987},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc51166.2024.10622929","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc51166.2024.10622929","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2024 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1382364851","display_name":null,"funder_award_id":"62101295","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1600744878","https://openalex.org/W2005956500","https://openalex.org/W2072550346","https://openalex.org/W2114267371","https://openalex.org/W2147576921","https://openalex.org/W2162844151","https://openalex.org/W2194775991","https://openalex.org/W2272847350","https://openalex.org/W2541876556","https://openalex.org/W2602923095","https://openalex.org/W2752782242","https://openalex.org/W2773170971","https://openalex.org/W2963452667","https://openalex.org/W2963809753","https://openalex.org/W2977117446","https://openalex.org/W3034552520","https://openalex.org/W4232120769","https://openalex.org/W4288366796","https://openalex.org/W4316655748","https://openalex.org/W4323338327","https://openalex.org/W4375869042","https://openalex.org/W6751512325","https://openalex.org/W6779547538"],"related_works":["https://openalex.org/W2387796150","https://openalex.org/W1976985527","https://openalex.org/W2052116765","https://openalex.org/W2381960863","https://openalex.org/W1990319978","https://openalex.org/W2354034738","https://openalex.org/W2386722878","https://openalex.org/W1963716487","https://openalex.org/W2382303592","https://openalex.org/W4225155218"],"abstract_inverted_index":{"Automatic":[0],"modulation":[1,8,31],"recognition":[2,10,32,73],"(AMR)":[3],"is":[4],"crucial":[5],"for":[6,93],"efficient":[7],"type":[9],"in":[11,82,127],"modern":[12],"wireless":[13],"systems,":[14],"but":[15],"its":[16,38],"performance":[17,125],"suffers":[18],"from":[19,60],"low":[20,76,128],"signal-to-noise":[21],"ratios":[22],"(SNR).":[23],"This":[24],"paper":[25],"proposes":[26],"an":[27,42],"adaptive":[28,43,116],"denoising":[29,44,117],"automatic":[30],"network":[33],"(AD-AMR":[34],"Net)":[35],"to":[36,47,56,65],"improve":[37],"performance,":[39],"which":[40],"incorporates":[41],"module":[45,54],"(ADM)":[46],"alleviate":[48],"noise":[49],"and":[50,119],"a":[51],"feature":[52,121],"extraction":[53,122],"(FEM)":[55],"extract":[57],"multi-scale":[58,120],"features":[59],"the":[61,83,97,104],"denoised":[62],"signals.":[63],"Com-pared":[64],"conventional":[66,94],"AMR":[67],"schemes,":[68],"AD-AMR":[69],"Net":[70],"demonstrates":[71],"better":[72],"accuracy":[74,81,102],"under":[75],"SNRs,":[77],"achieving":[78],"84.8%":[79],"average":[80],"0":[84],"\u2013":[85,91],"10":[86],"dB":[87],"range":[88],"versus":[89],"80":[90],"82%":[92],"methods.":[95],"Overall,":[96],"proposed":[98],"model":[99],"achieves":[100],"64.6%":[101],"on":[103],"RadioML":[105],"dataset,":[106],"substantially":[107],"outperforming":[108],"previous":[109],"deep":[110],"learning":[111],"techniques.":[112],"Key":[113],"innovations":[114],"of":[115],"approach":[118],"enable":[123],"major":[124],"gains":[126],"SNR":[129],"scenarios.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}