{"id":"https://openalex.org/W3192979321","doi":"https://doi.org/10.1109/lcomm.2021.3098235","title":"Robust Methods for Wideband Compressive Spectrum Sensing Under Non-Gaussian Noise","display_name":"Robust Methods for Wideband Compressive Spectrum Sensing Under Non-Gaussian Noise","publication_year":2021,"publication_date":"2021-08-10","ids":{"openalex":"https://openalex.org/W3192979321","doi":"https://doi.org/10.1109/lcomm.2021.3098235","mag":"3192979321"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2021.3098235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2021.3098235","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-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/A5082734171","display_name":"Bandaru Bhavana","orcid":"https://orcid.org/0000-0003-0844-4661"},"institutions":[{"id":"https://openalex.org/I36893310","display_name":"University of Hyderabad","ror":"https://ror.org/04a7rxb17","country_code":"IN","type":"education","lineage":["https://openalex.org/I36893310"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bandaru Bhavana","raw_affiliation_strings":["Centre for Advanced Studies in Electronics Science and Technology, School of Physics, University of Hyderabad, Hyderabad, India"],"raw_orcid":"https://orcid.org/0000-0003-0844-4661","affiliations":[{"raw_affiliation_string":"Centre for Advanced Studies in Electronics Science and Technology, School of Physics, University of Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I36893310"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014087539","display_name":"Swetha Namburu","orcid":"https://orcid.org/0000-0001-6364-4207"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Swetha Namburu","raw_affiliation_strings":["Department of Electronics and Communication Engineering (ECE), GRIET, Hyderabad, India"],"raw_orcid":"https://orcid.org/0000-0001-6364-4207","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering (ECE), GRIET, Hyderabad, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051610178","display_name":"Trilochan Panigrahi","orcid":"https://orcid.org/0000-0003-0369-1532"},"institutions":[{"id":"https://openalex.org/I4210109276","display_name":"National Institute of Technology Goa","ror":"https://ror.org/01vmfpj79","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210109276"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Trilochan Panigrahi","raw_affiliation_strings":["Department of Electronics and Communication Engineering (ECE), National Institute of Technology Goa, Ponda, India"],"raw_orcid":"https://orcid.org/0000-0003-0369-1532","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering (ECE), National Institute of Technology Goa, Ponda, India","institution_ids":["https://openalex.org/I4210109276"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007129673","display_name":"Samrat L. Sabat","orcid":"https://orcid.org/0000-0002-1197-2943"},"institutions":[{"id":"https://openalex.org/I36893310","display_name":"University of Hyderabad","ror":"https://ror.org/04a7rxb17","country_code":"IN","type":"education","lineage":["https://openalex.org/I36893310"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Samrat L. Sabat","raw_affiliation_strings":["Centre for Advanced Studies in Electronics Science and Technology, School of Physics, University of Hyderabad, Hyderabad, India"],"raw_orcid":"https://orcid.org/0000-0002-1197-2943","affiliations":[{"raw_affiliation_string":"Centre for Advanced Studies in Electronics Science and Technology, School of Physics, University of Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I36893310"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8985,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.84268146,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"25","issue":"10","first_page":"3398","last_page":"3402"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T12146","display_name":"Power Line Communications and Noise","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/wideband","display_name":"Wideband","score":0.7184998989105225},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6093441247940063},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.591507077217102},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5481071472167969},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.46917039155960083},{"id":"https://openalex.org/keywords/spectrum","display_name":"Spectrum (functional analysis)","score":0.44364607334136963},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.3518337309360504},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32610124349594116},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.3245062828063965},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3201943039894104},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3107442259788513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21691587567329407},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1888493299484253},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1152026355266571}],"concepts":[{"id":"https://openalex.org/C2780202535","wikidata":"https://www.wikidata.org/wiki/Q4524457","display_name":"Wideband","level":2,"score":0.7184998989105225},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6093441247940063},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.591507077217102},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5481071472167969},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.46917039155960083},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.44364607334136963},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.3518337309360504},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32610124349594116},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.3245062828063965},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3201943039894104},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3107442259788513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21691587567329407},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1888493299484253},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1152026355266571},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2021.3098235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2021.3098235","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1981467637","https://openalex.org/W2006554558","https://openalex.org/W2030433189","https://openalex.org/W2048236741","https://openalex.org/W2286900311","https://openalex.org/W2789516494","https://openalex.org/W2950321066","https://openalex.org/W2965638029","https://openalex.org/W2979150572","https://openalex.org/W2991006268","https://openalex.org/W3150752166","https://openalex.org/W4229530126"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W3112081258","https://openalex.org/W4200358983","https://openalex.org/W1483997978","https://openalex.org/W2611619770","https://openalex.org/W2030974198"],"abstract_inverted_index":{"In":[0,73],"a":[1,34,47,87],"cognitive":[2],"radio":[3],"network,":[4],"non-reconstruction-based":[5],"wideband":[6],"compressive":[7],"spectrum":[8,38],"sensing":[9,39,79,127,164],"poses":[10],"challenges":[11],"under":[12,129],"the":[13,28,41,53,61,78,83,93,104,110,117,122,160],"non-Gaussian":[14,88],"noise":[15,26,45,65,89,108],"environment.":[16],"The":[17,100,155],"maximum":[18],"correntropy":[19],"criterion":[20],"(MCC)":[21],"is":[22,33,68,157],"robust":[23,98,101,126],"to":[24,70,120],"impulsive":[25,107],"whereas,":[27],"Parzen":[29],"window":[30],"Renyi":[31],"entropy":[32],"good":[35],"choice":[36],"for":[37,163],"in":[40,86,109],"presence":[42],"of":[43,56,63,81,106,125],"Gaussian":[44],"at":[46],"low":[48],"signal-to-noise":[49],"ratio":[50],"(SNR).":[51],"However,":[52],"detection":[54],"performance":[55,80,124,156],"these":[57],"algorithms":[58,85,128],"depends":[59],"on":[60],"accuracy":[62],"measured":[64],"variance,":[66],"which":[67],"sensitive":[69],"impulse":[71],"noise.":[72,154],"this":[74],"letter,":[75],"we":[76,114],"improve":[77],"both":[82,130],"aforementioned":[84],"environment":[90],"by":[91],"modifying":[92],"kernel":[94],"and":[95,133],"threshold":[96],"using":[97],"statistics.":[99],"technique":[102],"minimizes":[103],"influence":[105],"received":[111],"signal.":[112,169],"Finally,":[113],"carry":[115],"out":[116],"simulation":[118],"results":[119],"illustrate":[121],"superior":[123],"Bernoulli\u2019s":[131],"distribution":[132,152],"symmetric":[134],"<inline-formula":[135,144],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[136,145],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[137,146],"<tex-math":[138,147],"notation=\"LaTeX\">$\\alpha":[139],"$":[140],"</tex-math></inline-formula>":[141,150],"stable":[142],"(":[143],"notation=\"LaTeX\">$\\text{S}\\alpha":[148],"\\text{S}$":[149],")":[151],"channel":[153],"compared":[158],"with":[159],"non-robust":[161],"counterpart":[162],"multi-carrier":[165],"Universal-Filtered":[166],"Multi-Carrier":[167],"(UFMC)":[168]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}