{"id":"https://openalex.org/W2739532970","doi":"https://doi.org/10.1109/icc.2017.7996412","title":"Sigmoid function detector in the Presence of heavy-tailed noise for multiple antenna cognitive radio networks","display_name":"Sigmoid function detector in the Presence of heavy-tailed noise for multiple antenna cognitive radio networks","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2739532970","doi":"https://doi.org/10.1109/icc.2017.7996412","mag":"2739532970"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2017.7996412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2017.7996412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5079602365","display_name":"Mohammad Yavari Manesh","orcid":null},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad Yavari Manesh","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079339295","display_name":"Ali Olfat","orcid":"https://orcid.org/0000-0002-0246-8067"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ali Olfat","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran","institution_ids":["https://openalex.org/I23946033"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I23946033"],"apc_list":null,"apc_paid":null,"fwci":3.3721,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.93975104,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"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/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9976999759674072,"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"}},{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.8354066014289856},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7047998309135437},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6094276905059814},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5736721158027649},{"id":"https://openalex.org/keywords/limiter","display_name":"Limiter","score":0.4627957344055176},{"id":"https://openalex.org/keywords/detection-theory","display_name":"Detection theory","score":0.4329324960708618},{"id":"https://openalex.org/keywords/antenna","display_name":"Antenna (radio)","score":0.4322887659072876},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.43087685108184814},{"id":"https://openalex.org/keywords/noise-power","display_name":"Noise power","score":0.429939329624176},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.41580989956855774},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3603523075580597},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.340891569852829},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.32306092977523804},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.29550760984420776},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.25960177183151245},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2015095055103302},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1914125382900238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12688177824020386},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.07318079471588135}],"concepts":[{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.8354066014289856},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7047998309135437},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6094276905059814},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5736721158027649},{"id":"https://openalex.org/C45011657","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiter","level":2,"score":0.4627957344055176},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.4329324960708618},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.4322887659072876},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.43087685108184814},{"id":"https://openalex.org/C203234222","wikidata":"https://www.wikidata.org/wiki/Q2133519","display_name":"Noise power","level":3,"score":0.429939329624176},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.41580989956855774},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3603523075580597},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.340891569852829},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.32306092977523804},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.29550760984420776},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.25960177183151245},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2015095055103302},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1914125382900238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12688177824020386},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.07318079471588135},{"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/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc.2017.7996412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2017.7996412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1607663705","https://openalex.org/W2006067561","https://openalex.org/W2104169127","https://openalex.org/W2120191353","https://openalex.org/W2134230109","https://openalex.org/W2153782921","https://openalex.org/W2168078104","https://openalex.org/W2171402290","https://openalex.org/W2398781343","https://openalex.org/W2506285684","https://openalex.org/W3133603318","https://openalex.org/W4298032380","https://openalex.org/W6712260932"],"related_works":["https://openalex.org/W2378015512","https://openalex.org/W1974075201","https://openalex.org/W2153508596","https://openalex.org/W2135368825","https://openalex.org/W2036630609","https://openalex.org/W1980385416","https://openalex.org/W2135117342","https://openalex.org/W1853503676","https://openalex.org/W2441839663","https://openalex.org/W2081816685"],"abstract_inverted_index":{"An":[0],"efficient":[1],"spectrum":[2],"sensing":[3],"scheme":[4,126],"is":[5,20,29,61,76,94,135],"proposed":[6,46],"for":[7,89],"detecting":[8],"a":[9,14,54,64,136],"primary":[10,27],"signal":[11,28],"corrupted":[12],"by":[13,63],"Generalized":[15],"Gaussian":[16],"Noise":[17],"(GGN).":[18],"It":[19,93],"assumed":[21],"that":[22,98],"the":[23,26,33,68,80,86,99,122,128,139],"power":[24],"of":[25,70,83,91,130],"much":[30],"smaller":[31],"than":[32],"noise":[34],"power,":[35],"and":[36,121,141],"secondary":[37],"users":[38],"are":[39],"equipped":[40],"with":[41,113],"multiple":[42],"antenna":[43],"receivers.":[44],"The":[45,58,73],"scheme,":[47],"referred":[48],"to":[49,78],"as":[50,107],"sigmoid":[51,55,59,74,100],"detector,":[52],"uses":[53],"soft":[56,114],"limiter.":[57,72],"limiter":[60],"characterized":[62],"parameter":[65,75],"which":[66],"controls":[67],"softness":[69],"its":[71],"optimized":[77],"achieve":[79],"best":[81],"performance(probability":[82],"detection)":[84],"using":[85],"chernoff":[87],"bound":[88],"probability":[90],"detection.":[92],"shown":[95],"through":[96],"simulations":[97],"detector":[101],"outperforms":[102],"well":[103],"known":[104],"detectors":[105],"such":[106],"SL-PCA":[108],"(soft-limited":[109],"polarity":[110],"coincidence":[111,119],"array)":[112,120],"limiting":[115],"function,":[116],"PCA":[117],"(polarity":[118],"energy":[123],"detection":[124],"(ED)":[125],"in":[127],"presence":[129],"heavy-tailed":[131],"GGN.":[132],"Also,":[133],"there":[134],"match":[137],"between":[138],"simulation":[140],"analytical":[142],"results.":[143]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
