{"id":"https://openalex.org/W2958472174","doi":"https://doi.org/10.1109/icc.2019.8761949","title":"Decentralized Deep Reinforcement Learning for Delay-Power Tradeoff in Vehicular Communications","display_name":"Decentralized Deep Reinforcement Learning for Delay-Power Tradeoff in Vehicular Communications","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2958472174","doi":"https://doi.org/10.1109/icc.2019.8761949","mag":"2958472174"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2019.8761949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2019.8761949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2019 - 2019 IEEE International Conference on Communications (ICC)","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/A5065252700","display_name":"Xianfu Chen","orcid":"https://orcid.org/0000-0002-9453-4200"},"institutions":[{"id":"https://openalex.org/I87653560","display_name":"VTT Technical Research Centre of Finland","ror":"https://ror.org/04b181w54","country_code":"FI","type":"nonprofit","lineage":["https://openalex.org/I4210089493","https://openalex.org/I87653560"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Xianfu Chen","raw_affiliation_strings":["VTT Technical Research Centre of Finland, Finland"],"affiliations":[{"raw_affiliation_string":"VTT Technical Research Centre of Finland, Finland","institution_ids":["https://openalex.org/I87653560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046333931","display_name":"Celimuge Wu","orcid":"https://orcid.org/0000-0001-6853-5878"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Celimuge Wu","raw_affiliation_strings":["Graduate School of Informatics and Engineering, University of Electro- Communications, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics and Engineering, University of Electro- Communications, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100626780","display_name":"Honggang Zhang","orcid":"https://orcid.org/0000-0003-1492-1364"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honggang Zhang","raw_affiliation_strings":["College of Information Science and Electronic Engineering, Zhejiang University, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Electronic Engineering, Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456327","display_name":"Yan Zhang","orcid":"https://orcid.org/0000-0002-8561-5092"},"institutions":[{"id":"https://openalex.org/I184942183","display_name":"University of Oslo","ror":"https://ror.org/01xtthb56","country_code":"NO","type":"education","lineage":["https://openalex.org/I184942183"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Yan Zhang","raw_affiliation_strings":["Department of Informatics, University of Oslo, Norway"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, University of Oslo, Norway","institution_ids":["https://openalex.org/I184942183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061429095","display_name":"Mehdi Bennis","orcid":"https://orcid.org/0000-0003-0261-0171"},"institutions":[{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Mehdi Bennis","raw_affiliation_strings":["Centre for Wireless Communications, University of Oulu, Finland"],"affiliations":[{"raw_affiliation_string":"Centre for Wireless Communications, University of Oulu, Finland","institution_ids":["https://openalex.org/I98381234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054422379","display_name":"Heli Vuojala","orcid":null},"institutions":[{"id":"https://openalex.org/I87653560","display_name":"VTT Technical Research Centre of Finland","ror":"https://ror.org/04b181w54","country_code":"FI","type":"nonprofit","lineage":["https://openalex.org/I4210089493","https://openalex.org/I87653560"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Heli Vuojala","raw_affiliation_strings":["VTT Technical Research Centre of Finland, Finland"],"affiliations":[{"raw_affiliation_string":"VTT Technical Research Centre of Finland, Finland","institution_ids":["https://openalex.org/I87653560"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5065252700"],"corresponding_institution_ids":["https://openalex.org/I87653560"],"apc_list":null,"apc_paid":null,"fwci":0.4769,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.648671,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"518","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9991999864578247,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9987000226974487,"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/T11409","display_name":"Advanced Wireless Network Optimization","score":0.9976999759674072,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8606769442558289},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.8375606536865234},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8052074313163757},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.558357298374176},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5265990495681763},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.4977617561817169},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.48216575384140015},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4448452591896057},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.4401073455810547},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36415398120880127},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3281635046005249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28699833154678345},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2750120162963867}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8606769442558289},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.8375606536865234},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8052074313163757},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.558357298374176},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5265990495681763},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.4977617561817169},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.48216575384140015},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4448452591896057},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.4401073455810547},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36415398120880127},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3281635046005249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28699833154678345},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2750120162963867},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc.2019.8761949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2019.8761949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2019 - 2019 IEEE International Conference on Communications (ICC)","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":31,"referenced_works":["https://openalex.org/W1639877187","https://openalex.org/W2037353752","https://openalex.org/W2064675550","https://openalex.org/W2098105074","https://openalex.org/W2121092017","https://openalex.org/W2121863487","https://openalex.org/W2145339207","https://openalex.org/W2150339816","https://openalex.org/W2155968351","https://openalex.org/W2270147915","https://openalex.org/W2339875908","https://openalex.org/W2402144811","https://openalex.org/W2407584500","https://openalex.org/W2746553466","https://openalex.org/W2750212574","https://openalex.org/W2791639158","https://openalex.org/W2797178713","https://openalex.org/W2889999533","https://openalex.org/W2894383926","https://openalex.org/W2947400732","https://openalex.org/W2953384591","https://openalex.org/W2955535572","https://openalex.org/W2962846391","https://openalex.org/W2962938178","https://openalex.org/W2963250023","https://openalex.org/W3139377883","https://openalex.org/W4214717370","https://openalex.org/W6677939520","https://openalex.org/W6713134421","https://openalex.org/W6754568357","https://openalex.org/W6754611814"],"related_works":["https://openalex.org/W2808418668","https://openalex.org/W2357975469","https://openalex.org/W2101748387","https://openalex.org/W3096874164","https://openalex.org/W2807018115","https://openalex.org/W4388236136","https://openalex.org/W4281812492","https://openalex.org/W3105579180","https://openalex.org/W4200250224","https://openalex.org/W2970347269"],"abstract_inverted_index":{"This":[0],"paper":[1],"targets":[2],"at":[3,133,154],"the":[4,22,27,79,85,108,122,125,146,150,155,160,165,168],"problem":[5],"of":[6,69,90,110,149,167],"radio":[7],"resource":[8],"management":[9],"for":[10,37],"expected":[11],"long-term":[12],"delay-power":[13],"tradeoff":[14],"in":[15,58,74,113,139,143],"vehicular":[16],"communications.":[17],"At":[18],"each":[19,118,134],"decision":[20,52,132],"epoch,":[21],"road":[23],"side":[24],"unit":[25],"observes":[26],"global":[28,151],"network":[29,152],"state,":[30],"allocates":[31],"channels":[32],"and":[33,71,129,163],"schedules":[34],"data":[35,75],"packets":[36],"all":[38],"vehicle":[39],"user":[40],"equipment-pairs":[41],"(VUE-pairs).":[42],"The":[43,55],"decision-making":[44,80],"procedure":[45],"is":[46],"modelled":[47],"as":[48],"a":[49,88,140],"discrete-time":[50],"Markov":[51],"process":[53],"(MDP).":[54],"technical":[56],"challenges":[57],"solving":[59],"an":[60,96],"optimal":[61,126],"control":[62],"policy":[63],"originate":[64],"from":[65],"highly":[66],"spatial":[67],"mobility":[68],"vehicles":[70],"temporal":[72],"variations":[73],"traffic.":[76],"To":[77],"simplify":[78],"process,":[81],"we":[82],"first":[83],"decompose":[84],"MDP":[86],"into":[87],"series":[89],"per-VUE-pair":[91,119],"MDPs.":[92],"We":[93],"then":[94],"propose":[95],"online":[97,170],"long":[98],"short-term":[99],"memory":[100],"based":[101],"deep":[102],"reinforcement":[103],"learning":[104,171],"algorithm":[105],"to":[106],"break":[107],"curse":[109],"high":[111],"dimensionality":[112],"state":[114,153],"space":[115],"faced":[116],"by":[117],"MDP.":[120],"With":[121],"proposed":[123,169],"algorithm,":[124],"channel":[127],"allocation":[128],"packet":[130],"scheduling":[131],"epoch":[135],"can":[136],"be":[137],"made":[138],"decentralized":[141],"way":[142],"accordance":[144],"with":[145],"partial":[147],"observations":[148],"VUE-pairs.":[156],"Numerical":[157],"simulations":[158],"validate":[159],"theoretical":[161],"analysis":[162],"show":[164],"effectiveness":[166],"algorithm.":[172]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
