{"id":"https://openalex.org/W2170705708","doi":"https://doi.org/10.1109/tsp.2009.2028970","title":"Algorithms for Dynamic Spectrum Access With Learning for Cognitive Radio","display_name":"Algorithms for Dynamic Spectrum Access With Learning for Cognitive Radio","publication_year":2009,"publication_date":"2009-08-07","ids":{"openalex":"https://openalex.org/W2170705708","doi":"https://doi.org/10.1109/tsp.2009.2028970","mag":"2170705708"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2009.2028970","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/0807.2677","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039592314","display_name":"Jayakrishnan Unnikrishnan","orcid":"https://orcid.org/0000-0002-8464-4641"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"funder","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Unnikrishnan","raw_affiliation_strings":["Coordinated Science Laboratory and the Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"Coordinated Science Laboratory and the Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067089715","display_name":"Venugopal V. Veeravalli","orcid":"https://orcid.org/0000-0001-5490-0037"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"funder","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"V.V. Veeravalli","raw_affiliation_strings":["Coordinated Science Laboratory and the Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"Coordinated Science Laboratory and the Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":22.319,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":133,"citation_normalized_percentile":{"value":0.976642,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"58","issue":"2","first_page":"750","last_page":"760"},"is_retracted":false,"is_paratext":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":0.9976,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9954,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.9124615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6627517},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.6431706},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5505932},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.53593224},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5183443},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.51023674},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5027814},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.46864197},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46325928},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.44395825},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.40143436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2679118},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.25169545},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17825243},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.13978502},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11367369},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2009.2028970","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/0807.2677","pdf_url":"https://arxiv.org/pdf/0807.2677","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/0807.2677","pdf_url":"http://arxiv.org/pdf/0807.2677","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":null,"pdf_url":"http://arxiv.org/pdf/0807.2677v2.pdf","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/0807.2677","pdf_url":"https://arxiv.org/pdf/0807.2677","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.75}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":11,"referenced_works":["https://openalex.org/W1590772317","https://openalex.org/W1972679863","https://openalex.org/W2028640608","https://openalex.org/W2029199203","https://openalex.org/W2098432798","https://openalex.org/W2107441100","https://openalex.org/W2118726574","https://openalex.org/W2142819538","https://openalex.org/W2170725991","https://openalex.org/W2171671264","https://openalex.org/W3133603318"],"related_works":["https://openalex.org/W52153049","https://openalex.org/W2951545791","https://openalex.org/W2693773189","https://openalex.org/W2298116686","https://openalex.org/W2176656248","https://openalex.org/W2116441277","https://openalex.org/W2096013579","https://openalex.org/W1760611253","https://openalex.org/W1589140671","https://openalex.org/W1526281004"],"abstract_inverted_index":{"":[2],"We":[3,45,98,136,155,181,199],"study":[4],"the":[5,48,51,58,61,66,83,91,107,110,125,139,144,148,151,161,170,175,178,187,197,205,208],"problem":[6],"of":[7,27,57,60,93,109,147,207],"dynamic":[8],"spectrum":[9],"sensing":[10],"and":[11,78,128,163],"access":[12,79],"in":[13,35],"cognitive":[14,28,52],"radio":[15],"systems":[16],"as":[17],"a":[18,42,74,88,157,192,202],"partially":[19],"observed":[20],"Markov":[21],"decision":[22],"process":[23],"(POMDP).":[24],"A":[25],"group":[26],"users":[29,53],"cooperatively":[30],"tries":[31],"to":[32,124,132],"exploit":[33],"vacancies":[34],"primary":[36,67,152],"(licensed)":[37],"channels":[38],"whose":[39],"occupancies":[40],"follow":[41],"Markovian":[43],"evolution.":[44],"first":[46],"consider":[47,138],"scenario":[49,142],"where":[50,143],"have":[54],"perfect":[55],"knowledge":[56],"distribution":[59,146,162],"signals":[62],"they":[63],"receive":[64],"from":[65,150],"users.":[68],"For":[69],"this":[70,184],"problem,":[71],"we":[72,115],"obtain":[73],"greedy":[75],"channel":[76],"selection":[77],"policy":[80],"that":[81,117,167,183,190],"maximizes":[82],"instantaneous":[84],"reward,":[85],"while":[86],"satisfying":[87],"constraint":[89,176],"on":[90,106,177],"probability":[92],"interfering":[94],"with":[95],"licensed":[96],"transmissions.":[97],"also":[99,200],"derive":[100],"an":[101,133,165],"analytical":[102],"universal":[103],"upper":[104,126],"bound":[105,127],"performance":[108,122,130],"optimal":[111],"policy.":[112],"Through":[113],"simulation,":[114],"show":[116,182],"our":[118],"scheme":[119],"achieves":[120],"good":[121],"relative":[123,131],"improved":[129],"existing":[134],"scheme.":[135],"then":[137],"more":[140],"practical":[141],"exact":[145],"signal":[149],"is":[153],"unknown.":[154],"assume":[156],"parametric":[158],"model":[159],"for":[160,196,204],"develop":[164],"algorithm":[166,185],"can":[168],"learn":[169],"true":[171],"distribution,":[172],"still":[173],"guaranteeing":[174],"interference":[179],"probability.":[180],"outperforms":[186],"naive":[188],"design":[189],"assumes":[191],"worst":[193],"case":[194],"value":[195],"parameter.":[198],"provide":[201],"proof":[203],"convergence":[206],"learning":[209],"algorithm.":[210],"":[211]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2170705708","counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":24},{"year":2013,"cited_by_count":15},{"year":2012,"cited_by_count":31}],"updated_date":"2025-03-18T12:50:05.837949","created_date":"2016-06-24"}