{"id":"https://openalex.org/W4406267009","doi":"https://doi.org/10.1109/vtc2024-fall63153.2024.10757676","title":"Traffic Distribution Generation Considering Spatial Continuity for Base Station Sleep Control","display_name":"Traffic Distribution Generation Considering Spatial Continuity for Base Station Sleep Control","publication_year":2024,"publication_date":"2024-10-07","ids":{"openalex":"https://openalex.org/W4406267009","doi":"https://doi.org/10.1109/vtc2024-fall63153.2024.10757676"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2024-fall63153.2024.10757676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2024-fall63153.2024.10757676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)","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/A5016398372","display_name":"Natsuki Morita","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Natsuki Morita","raw_affiliation_strings":["Fujitsu Limited,Artificial Intelligence Laboratory,Kawasaki,Japan"],"affiliations":[{"raw_affiliation_string":"Fujitsu Limited,Artificial Intelligence Laboratory,Kawasaki,Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026150925","display_name":"Yoshihiro Okawa","orcid":"https://orcid.org/0000-0001-5095-4927"},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshihiro Okawa","raw_affiliation_strings":["Fujitsu Limited,Artificial Intelligence Laboratory,Kawasaki,Japan"],"affiliations":[{"raw_affiliation_string":"Fujitsu Limited,Artificial Intelligence Laboratory,Kawasaki,Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009433353","display_name":"Jun Kakuta","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jun Kakuta","raw_affiliation_strings":["Fujitsu Limited,Artificial Intelligence Laboratory,Kawasaki,Japan"],"affiliations":[{"raw_affiliation_string":"Fujitsu Limited,Artificial Intelligence Laboratory,Kawasaki,Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104087241","display_name":"Masatoshi Ogawa","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masatoshi Ogawa","raw_affiliation_strings":["Fujitsu Limited,Artificial Intelligence Laboratory,Kawasaki,Japan"],"affiliations":[{"raw_affiliation_string":"Fujitsu Limited,Artificial Intelligence Laboratory,Kawasaki,Japan","institution_ids":["https://openalex.org/I2252096349"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016398372"],"corresponding_institution_ids":["https://openalex.org/I2252096349"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2788296,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T12546","display_name":"Smart Parking Systems Research","score":0.8155999779701233,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12546","display_name":"Smart Parking Systems Research","score":0.8155999779701233,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T13924","display_name":"Internet of Things and Social Network Interactions","score":0.7562999725341797,"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/T12941","display_name":"Embedded Systems and FPGA Design","score":0.7473999857902527,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/computer-science","display_name":"Computer science","score":0.6438009738922119},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.6107305288314819},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.4345545768737793},{"id":"https://openalex.org/keywords/sleep","display_name":"Sleep (system call)","score":0.4173396825790405},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.3264320492744446},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12065112590789795}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6438009738922119},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.6107305288314819},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.4345545768737793},{"id":"https://openalex.org/C2775841894","wikidata":"https://www.wikidata.org/wiki/Q4683692","display_name":"Sleep (system call)","level":2,"score":0.4173396825790405},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.3264320492744446},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12065112590789795},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2024-fall63153.2024.10757676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2024-fall63153.2024.10757676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Base":[0],"station":[1],"(BS)":[2],"sleep":[3,187],"control":[4,27,188],"with":[5,20,80],"reinforcement":[6],"learning":[7],"(RL)":[8],"offers":[9],"a":[10,51,90,158],"promising":[11],"way":[12],"to":[13,67,104,177],"operate":[14],"5G":[15],"radio":[16],"access":[17],"networks":[18],"efficiently":[19],"low":[21],"power":[22],"consumption.":[23],"For":[24],"the":[25,29,73,81,94,100,113,122,129,145,152,163,169,172,183,192],"optimal":[26],"considering":[28],"channel":[30],"quality,":[31],"an":[32,46],"accurate":[33],"and":[34,58,85,120],"high-resolution":[35,52],"spatial":[36,53,75,115,123,147,194],"traffic":[37,54,76,118,139,148,174,195],"distribution":[38,55,77],"is":[39],"required.":[40],"In":[41],"this":[42],"study,":[43],"we":[44,111,156,181],"propose":[45],"effective":[47],"method":[48],"for":[49],"generating":[50],"using":[56,138],"throughput":[57,84],"load":[59,86],"data":[60,63,140],"per":[61,87],"BS,":[62],"typically":[64],"readily":[65],"available":[66,95],"network":[68],"operators.":[69],"Our":[70,134],"approach":[71],"ensures":[72],"generated":[74,146,193],"aligns":[78],"closely":[79,150],"actual":[82],"measured":[83],"BS.":[88],"However,":[89],"challenge":[91],"arises":[92],"when":[93],"measurements":[96],"are":[97],"fewer":[98],"than":[99],"unknown":[101],"variables,":[102],"leading":[103],"multiple":[105],"possible":[106,132],"solutions.":[107,133],"To":[108],"overcome":[109],"this,":[110],"leverage":[112],"inherent":[114],"correlation":[116],"of":[117,125,131,185],"amounts":[119],"assume":[121],"continuity":[124],"traffic,":[126],"thus":[127],"constraining":[128],"range":[130],"simulation":[135],"studies,":[136],"conducted":[137],"from":[141],"Milan,":[142],"confirm":[143],"that":[144],"distributions":[149],"mirror":[151],"original":[153],"ones.":[154],"Specifically,":[155],"observe":[157],"10.3":[159],"%":[160],"improvement":[161],"in":[162,168],"root":[164],"mean":[165],"squared":[166],"error":[167],"area":[170],"experiencing":[171],"highest":[173],"volumes,":[175],"compared":[176],"traditional":[178],"method.":[179],"Furthermore,":[180],"evaluate":[182],"performance":[184],"BS":[186],"by":[189],"RL,":[190],"utilizing":[191],"distributions.":[196]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
