{"id":"https://openalex.org/W2837805563","doi":"https://doi.org/10.1109/iccw.2018.8403658","title":"Deep Reinforcement Learning Approach to QoE-Driven Resource Allocation for Spectrum Underlay in Cognitive Radio Networks","display_name":"Deep Reinforcement Learning Approach to QoE-Driven Resource Allocation for Spectrum Underlay in Cognitive Radio Networks","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2837805563","doi":"https://doi.org/10.1109/iccw.2018.8403658","mag":"2837805563"},"language":"en","primary_location":{"id":"doi:10.1109/iccw.2018.8403658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccw.2018.8403658","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications Workshops (ICC Workshops)","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/A5011716722","display_name":"Fatemeh Shah-Mohammadi","orcid":"https://orcid.org/0000-0002-9034-7803"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fatemeh Shah-Mohammadi","raw_affiliation_strings":["Rochester institute of Technology, Rochester, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester institute of Technology, Rochester, New York, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031417073","display_name":"Andres Kwasinski","orcid":"https://orcid.org/0000-0002-8083-8318"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andres Kwasinski","raw_affiliation_strings":["Rochester institute of Technology, Rochester, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester institute of Technology, Rochester, New York, USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155173764"],"apc_list":null,"apc_paid":null,"fwci":3.6189,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.94177633,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"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":0.9998000264167786,"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":0.9998000264167786,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9975000023841858,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8613089323043823},{"id":"https://openalex.org/keywords/underlay","display_name":"Underlay","score":0.821368932723999},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.778205394744873},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.7397308349609375},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.6394307017326355},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5649349689483643},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46425941586494446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46317747235298157},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.4504939615726471},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4196639955043793},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.41724294424057007},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38171011209487915},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34347766637802124},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.328707218170166},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.17431485652923584},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.15234366059303284},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10916760563850403},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09367990493774414},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0895276665687561}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8613089323043823},{"id":"https://openalex.org/C2777679929","wikidata":"https://www.wikidata.org/wiki/Q7883709","display_name":"Underlay","level":3,"score":0.821368932723999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.778205394744873},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.7397308349609375},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.6394307017326355},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5649349689483643},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46425941586494446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46317747235298157},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.4504939615726471},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4196639955043793},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.41724294424057007},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38171011209487915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34347766637802124},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.328707218170166},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.17431485652923584},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.15234366059303284},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10916760563850403},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09367990493774414},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0895276665687561},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccw.2018.8403658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccw.2018.8403658","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications Workshops (ICC Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W67225717","https://openalex.org/W391985582","https://openalex.org/W1496659747","https://openalex.org/W1575384945","https://openalex.org/W1965403711","https://openalex.org/W2003983810","https://openalex.org/W2050466752","https://openalex.org/W2054504694","https://openalex.org/W2090616925","https://openalex.org/W2117987129","https://openalex.org/W2121863487","https://openalex.org/W2134142361","https://openalex.org/W2143225747","https://openalex.org/W2145339207","https://openalex.org/W2161907179","https://openalex.org/W2257979135","https://openalex.org/W2553535241","https://openalex.org/W2759880155","https://openalex.org/W2761694337","https://openalex.org/W2776600972","https://openalex.org/W2963658727","https://openalex.org/W4214717370","https://openalex.org/W6634534149","https://openalex.org/W6745170832"],"related_works":["https://openalex.org/W4255303560","https://openalex.org/W1975029702","https://openalex.org/W1943171502","https://openalex.org/W2744240346","https://openalex.org/W2077074280","https://openalex.org/W4390189335","https://openalex.org/W2769590643","https://openalex.org/W2169642774","https://openalex.org/W2532161418","https://openalex.org/W2556201531"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,67,80],"deep":[4,75],"reinforcement":[5,76],"learning-based":[6],"technique":[7],"for":[8,114],"cognitive":[9],"radio":[10],"underlay":[11],"dynamic":[12],"spectrum":[13],"access":[14],"(DSA)":[15],"that":[16,106],"performs":[17],"distributed":[18],"joint":[19],"multi-resource":[20],"allocation":[21,55,61],"to":[22,30,83,99,122],"satisfy":[23],"the":[24,32,38,85,90,100,110,123],"primary":[25],"link":[26],"interference":[27],"constraint":[28],"and":[29,79,119,130],"maximize":[31],"secondary":[33],"network":[34,82],"performance,":[35],"measured":[36],"through":[37],"Mean":[39],"Opinion":[40],"Score":[41],"(MOS)":[42],"metric.":[43],"The":[44,59],"use":[45],"of":[46,56,112],"MOS":[47],"as":[48],"performance":[49],"metric":[50],"enables":[51],"seamless":[52],"integrated":[53],"resource":[54,60],"dissimilar":[57],"traffic.":[58],"problem":[62],"is":[63,93],"solved":[64],"by":[65,95,116],"utilizing":[66,127],"Deep":[68],"Q-":[69,132],"Network":[70],"(DQN)":[71],"algorithm,":[72],"an":[73],"advanced":[74],"learning":[77,91,98,101,108,129],"approach,":[78],"neural":[81],"approximate":[84],"Q":[86],"action-value":[87],"function.":[88],"Moreover,":[89],"process":[92],"improved":[94],"incorporating":[96],"transfer":[97,107,128],"procedure.":[102],"Simulation":[103],"results":[104],"show":[105],"reduces":[109],"number":[111],"iterations":[113],"convergence":[115],"approximately":[117],"25%":[118],"72%":[120],"compared":[121],"DQN-":[124],"algorithm":[125],"without":[126],"standard":[131],"learning,":[133],"respectively.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
