{"id":"https://openalex.org/W2133066402","doi":"https://doi.org/10.1109/iccve.2013.6799880","title":"Analytical and learning-based spectrum sensing over channels with both fading and shadowing","display_name":"Analytical and learning-based spectrum sensing over channels with both fading and shadowing","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2133066402","doi":"https://doi.org/10.1109/iccve.2013.6799880","mag":"2133066402"},"language":"en","primary_location":{"id":"doi:10.1109/iccve.2013.6799880","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccve.2013.6799880","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Connected Vehicles and Expo (ICCVE)","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/A5085871362","display_name":"Alireza Bagheri","orcid":"https://orcid.org/0000-0002-6556-3889"},"institutions":[{"id":"https://openalex.org/I928334797","display_name":"Semnan University","ror":"https://ror.org/029gksw03","country_code":"IR","type":"education","lineage":["https://openalex.org/I928334797"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Alireza Bagheri","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Semnan, Semnan, Iran","Dept. of Electr. & Comput. Eng., Univ. of Semnan, Semnan, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Semnan, Semnan, Iran","institution_ids":["https://openalex.org/I928334797"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Semnan, Semnan, Iran","institution_ids":["https://openalex.org/I928334797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015021192","display_name":"Ali Shahini","orcid":"https://orcid.org/0000-0001-9586-7966"},"institutions":[{"id":"https://openalex.org/I928334797","display_name":"Semnan University","ror":"https://ror.org/029gksw03","country_code":"IR","type":"education","lineage":["https://openalex.org/I928334797"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ali Shahini","raw_affiliation_strings":["Dept. of Electr. & Comput. Eng., Univ. of Semnan, Semnan, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Semnan, Semnan, Iran","institution_ids":["https://openalex.org/I928334797"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076113665","display_name":"Ali Shahzadi","orcid":"https://orcid.org/0000-0001-6159-3792"},"institutions":[{"id":"https://openalex.org/I928334797","display_name":"Semnan University","ror":"https://ror.org/029gksw03","country_code":"IR","type":"education","lineage":["https://openalex.org/I928334797"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ali Shahzadi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Semnan, Semnan, Iran","Dept. of Electr. & Comput. Eng., Univ. of Semnan, Semnan, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Semnan, Semnan, Iran","institution_ids":["https://openalex.org/I928334797"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Semnan, Semnan, Iran","institution_ids":["https://openalex.org/I928334797"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0181,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.92281717,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"20","issue":null,"first_page":"699","last_page":"706"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9997000098228455,"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":0.9925000071525574,"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/fading","display_name":"Fading","score":0.8928972482681274},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.7543290853500366},{"id":"https://openalex.org/keywords/nakagami-distribution","display_name":"Nakagami distribution","score":0.6105836033821106},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5980029702186584},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5602256059646606},{"id":"https://openalex.org/keywords/fusion-rules","display_name":"Fusion rules","score":0.5362692475318909},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4967568516731262},{"id":"https://openalex.org/keywords/shadow-mapping","display_name":"Shadow mapping","score":0.4860377907752991},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4670281410217285},{"id":"https://openalex.org/keywords/maximal-ratio-combining","display_name":"Maximal-ratio combining","score":0.4163692593574524},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.3827768564224243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3565042018890381},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2866448163986206},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27640336751937866},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.19937893748283386},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.13049528002738953},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.07313492894172668}],"concepts":[{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.8928972482681274},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.7543290853500366},{"id":"https://openalex.org/C115098869","wikidata":"https://www.wikidata.org/wiki/Q3258347","display_name":"Nakagami distribution","level":4,"score":0.6105836033821106},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5980029702186584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5602256059646606},{"id":"https://openalex.org/C2778971668","wikidata":"https://www.wikidata.org/wiki/Q5510284","display_name":"Fusion rules","level":4,"score":0.5362692475318909},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4967568516731262},{"id":"https://openalex.org/C116544410","wikidata":"https://www.wikidata.org/wiki/Q1478122","display_name":"Shadow mapping","level":2,"score":0.4860377907752991},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4670281410217285},{"id":"https://openalex.org/C86024645","wikidata":"https://www.wikidata.org/wiki/Q6795632","display_name":"Maximal-ratio combining","level":4,"score":0.4163692593574524},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3827768564224243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3565042018890381},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2866448163986206},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27640336751937866},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.19937893748283386},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.13049528002738953},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.07313492894172668},{"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/iccve.2013.6799880","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccve.2013.6799880","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Connected Vehicles and Expo (ICCVE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1525038591","https://openalex.org/W1533556785","https://openalex.org/W1535810436","https://openalex.org/W1536719366","https://openalex.org/W1601490018","https://openalex.org/W1969000844","https://openalex.org/W2002011878","https://openalex.org/W2008789311","https://openalex.org/W2013937720","https://openalex.org/W2031211320","https://openalex.org/W2031463285","https://openalex.org/W2039818336","https://openalex.org/W2062035544","https://openalex.org/W2066958484","https://openalex.org/W2076683887","https://openalex.org/W2096290492","https://openalex.org/W2101840010","https://openalex.org/W2111441999","https://openalex.org/W2141860157","https://openalex.org/W2144369278","https://openalex.org/W2150397642","https://openalex.org/W2153804803","https://openalex.org/W2155999145","https://openalex.org/W2164701487","https://openalex.org/W2165202277","https://openalex.org/W2166401126","https://openalex.org/W2168078104","https://openalex.org/W2215833482","https://openalex.org/W2296618885","https://openalex.org/W2482792214","https://openalex.org/W3113221786","https://openalex.org/W4235042061"],"related_works":["https://openalex.org/W2028647421","https://openalex.org/W1931268314","https://openalex.org/W963198203","https://openalex.org/W2110119741","https://openalex.org/W2962798278","https://openalex.org/W2165421096","https://openalex.org/W3144710960","https://openalex.org/W2155558773","https://openalex.org/W1543643734","https://openalex.org/W2125445053"],"abstract_inverted_index":{"In":[0,94,129],"this":[1,130],"paper,":[2],"sensing":[3],"performance":[4,80,170],"of":[5,81,144,152,171],"an":[6],"energy":[7],"detector":[8],"(ED)":[9],"for":[10,39,52,57,103],"local":[11],"and":[12,25,43,60,76,112,164],"collaborative":[13],"detection":[14,55],"scenarios":[15],"is":[16,30,65,127,139],"investigated":[17],"in":[18],"unreliable":[19],"environments":[20],"dominated":[21],"by":[22,32,161],"multipath":[23,41],"fading":[24,42,59],"shadowing":[26],"effects.":[27],"The":[28,63,79,156],"channel":[29],"modeled":[31],"using":[33],"K":[34],"<sub":[35],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[36],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">G</sub>":[37],"distribution":[38],"Nakagami-m":[40],"lognormal":[44],"shadowing.":[45],"Novel":[46],"analytical":[47,99,157],"expressions":[48,100],"are":[49,101,159],"firstly":[50],"derived":[51,102],"the":[53,69,86,98,133,145,169,172],"average":[54],"probability":[56],"both":[58],"fading/shadowing":[61],"cases.":[62],"analysis":[64],"then":[66],"extended":[67],"to":[68,141],"conventional":[70],"fusion":[71,75,83,89,96,120,131,175],"strategies":[72],"i.e.":[73],"decision":[74,82,147],"data":[77,95],"fusion.":[78],"scheme":[84,121],"under":[85],"generalized":[87],"k-out-of-n":[88],"rule":[90],"has":[91],"been":[92],"investigated.":[93],"method,":[97],"two":[104],"combining":[105,110,115],"schemes":[106],"including":[107],"maximal":[108],"ratio":[109],"(MRC)":[111],"square":[113],"law":[114],"(SLC).":[116],"Further,":[117],"a":[118,124],"reliable":[119],"based":[122],"on":[123],"learning":[125],"algorithm":[126,138],"proposed.":[128],"mechanism,":[132],"Least":[134],"Mean":[135],"Square":[136],"(LMS)":[137],"utilized":[140],"enhance":[142],"reliability":[143],"final":[146],"regarding":[148],"presence":[149],"or":[150],"absence":[151],"primary":[153],"user":[154],"(PU).":[155],"results":[158],"validated":[160],"numerical":[162],"computations":[163],"Monte-Carlo":[165],"simulations":[166],"along":[167],"with":[168],"proposed":[173],"learning-based":[174],"scheme.":[176]},"counts_by_year":[{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
