{"id":"https://openalex.org/W2584753519","doi":"https://doi.org/10.1109/glocom.2016.7842379","title":"Weighted Correlation-Based Spectrum Sensing for Cognitive Radio in Rayleigh Fading Channels","display_name":"Weighted Correlation-Based Spectrum Sensing for Cognitive Radio in Rayleigh Fading Channels","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2584753519","doi":"https://doi.org/10.1109/glocom.2016.7842379","mag":"2584753519"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2016.7842379","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2016.7842379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Communications Conference (GLOBECOM)","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/A5100352767","display_name":"Xinyu Wang","orcid":"https://orcid.org/0000-0001-6621-5598"},"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":"Xinyu Wang","raw_affiliation_strings":["Communication Research Center, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication Research Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006740084","display_name":"Min Jia","orcid":"https://orcid.org/0000-0003-3551-8654"},"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":"Min Jia","raw_affiliation_strings":["Communication Research Center, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication Research Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046141922","display_name":"Qing Guo","orcid":"https://orcid.org/0000-0003-4209-5469"},"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":"Qing Guo","raw_affiliation_strings":["Communication Research Center, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication Research Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028868067","display_name":"Xuemai Gu","orcid":"https://orcid.org/0000-0002-6011-9885"},"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":"Xuemai Gu","raw_affiliation_strings":["Communication Research Center, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication Research Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.2525,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.47458609,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"16","issue":null,"first_page":"1","last_page":"6"},"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":1.0,"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":1.0,"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":0.9914000034332275,"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/T12146","display_name":"Power Line Communications and Noise","score":0.987500011920929,"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/cognitive-radio","display_name":"Cognitive radio","score":0.7745504379272461},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.7024337649345398},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6165539622306824},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6148871183395386},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5844923853874207},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5454556941986084},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5422403216362},{"id":"https://openalex.org/keywords/detection-theory","display_name":"Detection theory","score":0.5244096517562866},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5113201141357422},{"id":"https://openalex.org/keywords/correlation-function","display_name":"Correlation function (quantum field theory)","score":0.4910776615142822},{"id":"https://openalex.org/keywords/rayleigh-fading","display_name":"Rayleigh fading","score":0.4823826849460602},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.47049546241760254},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4103168845176697},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.40070608258247375},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2966234087944031},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26329392194747925},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.25759851932525635},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.20007523894309998},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15645471215248108},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11856046319007874},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.08229362964630127},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.07807737588882446}],"concepts":[{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.7745504379272461},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.7024337649345398},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6165539622306824},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6148871183395386},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5844923853874207},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5454556941986084},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5422403216362},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.5244096517562866},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5113201141357422},{"id":"https://openalex.org/C53622274","wikidata":"https://www.wikidata.org/wiki/Q2496679","display_name":"Correlation function (quantum field theory)","level":3,"score":0.4910776615142822},{"id":"https://openalex.org/C56985126","wikidata":"https://www.wikidata.org/wiki/Q854039","display_name":"Rayleigh fading","level":4,"score":0.4823826849460602},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.47049546241760254},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4103168845176697},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.40070608258247375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2966234087944031},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26329392194747925},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.25759851932525635},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.20007523894309998},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15645471215248108},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11856046319007874},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.08229362964630127},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.07807737588882446},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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":2,"locations":[{"id":"doi:10.1109/glocom.2016.7842379","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2016.7842379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"},{"id":"mag:2748533970","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/201702230938362936","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4300000071525574}],"awards":[],"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":10,"referenced_works":["https://openalex.org/W1966567171","https://openalex.org/W2057396481","https://openalex.org/W2071570957","https://openalex.org/W2085968158","https://openalex.org/W2095296473","https://openalex.org/W2119137700","https://openalex.org/W2135115617","https://openalex.org/W2156043963","https://openalex.org/W2165202277","https://openalex.org/W2170880428"],"related_works":["https://openalex.org/W2181410425","https://openalex.org/W2051888740","https://openalex.org/W2382279859","https://openalex.org/W3203708548","https://openalex.org/W2046691252","https://openalex.org/W2132580384","https://openalex.org/W1973050875","https://openalex.org/W2003835194","https://openalex.org/W2384472869","https://openalex.org/W2548828344"],"abstract_inverted_index":{"Correlation-based":[0],"algorithms":[1,68,140],"are":[2,57,141,154,166,176],"low-complexity":[3],"spectrum":[4,48],"sensing":[5,49],"methods":[6],"requiring":[7],"little":[8],"knowledge":[9],"on":[10,169],"primary":[11,110],"signals":[12,83,184],"or":[13,105],"noise":[14,145],"signals.":[15],"However,":[16],"their":[17,162],"detection":[18,55,63,124,152,199],"performance":[19,200],"severely":[20],"degrades":[21],"in":[22,39,92,156],"the":[23,62,72,76,93,99,107,123,157,170,187],"low":[24,30,158],"signal-to-noise":[25],"ratio":[26],"(SNR)":[27],"regime":[28],"with":[29,104,181,196],"signal":[31],"correlation,":[32],"which":[33],"happens":[34],"to":[35,59,89,116,131],"be":[36,132],"quite":[37],"common":[38],"practice.":[40],"In":[41],"this":[42],"paper,":[43],"a":[44,86],"weighted":[45],"correlation-":[46],"based":[47,168],"scheme":[50,56],"and":[51,75,84,119,151,161],"its":[52],"simplified":[53],"blind":[54],"proposed":[58,67,139,188],"effectively":[60],"improve":[61],"performance.":[64,125],"The":[65,126,137,147,174],"two":[66,135,138],"adequately":[69],"exploit":[70],"both":[71],"auto-":[73],"correlation":[74],"cross-correlation":[77],"function":[78],"statistical":[79],"characteristics":[80],"of":[81,96,101,109],"received":[82],"assign":[85],"proper":[87],"weight":[88],"each":[90],"term":[91],"test":[94,102],"statistics":[95,103],"them,":[97],"enlarging":[98],"differences":[100],"without":[106],"existence":[108],"users":[111],"(PUs),":[112],"making":[113],"it":[114],"easier":[115],"detect":[117],"PUs":[118],"thus":[120],"greatly":[121],"promoting":[122],"weighting":[127],"operation":[128],"is":[129],"verified":[130,177],"effective":[133],"from":[134],"aspects.":[136],"proved":[142],"robust":[143],"against":[144],"uncertainty.":[146],"false":[148],"alarm":[149],"probabilities":[150,153],"analyzed":[155],"SNR":[159],"regime,":[160],"approximate":[163],"analytical":[164],"expressions":[165],"derived":[167],"central":[171],"limit":[172],"theorem.":[173],"analyses":[175],"through":[178],"simulations.":[179],"Experiments":[180],"simulated":[182],"multi-antenna":[183],"show":[185],"that":[186],"detectors":[189,195],"can":[190],"significantly":[191],"outperform":[192],"other":[193],"correlation-based":[194],"about":[197],"2.2-dB":[198],"gain.":[201]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}