{"id":"https://openalex.org/W3129005378","doi":"https://doi.org/10.1109/tnet.2021.3053771","title":"Deep Reinforcement Learning With Spatio-Temporal Traffic Forecasting for Data-Driven Base Station Sleep Control","display_name":"Deep Reinforcement Learning With Spatio-Temporal Traffic Forecasting for Data-Driven Base Station Sleep Control","publication_year":2021,"publication_date":"2021-01-29","ids":{"openalex":"https://openalex.org/W3129005378","doi":"https://doi.org/10.1109/tnet.2021.3053771","mag":"3129005378"},"language":"en","primary_location":{"id":"doi:10.1109/tnet.2021.3053771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnet.2021.3053771","pdf_url":null,"source":{"id":"https://openalex.org/S62238642","display_name":"IEEE/ACM Transactions on Networking","issn_l":"1063-6692","issn":["1063-6692","1558-2566"],"is_oa":false,"is_in_doaj":false,"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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Networking","raw_type":"journal-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/A5023787839","display_name":"Qiong Wu","orcid":"https://orcid.org/0000-0002-2156-4433"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiong Wu","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100647354","display_name":"Chen Xu","orcid":"https://orcid.org/0000-0002-0780-1607"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100760218","display_name":"Zhi Zhou","orcid":"https://orcid.org/0000-0002-0987-9344"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Zhou","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101957211","display_name":"Liang Chen","orcid":"https://orcid.org/0000-0002-3149-0239"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Chen","raw_affiliation_strings":["Department of Financial Technology, Tencent Inc., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Financial Technology, Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027033026","display_name":"Junshan Zhang","orcid":"https://orcid.org/0000-0002-3840-1753"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junshan Zhang","raw_affiliation_strings":["School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.0644,"has_fulltext":false,"cited_by_count":119,"citation_normalized_percentile":{"value":0.98244485,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"29","issue":"2","first_page":"935","last_page":"948"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9998000264167786,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9998000264167786,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.9955999851226807,"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/T12146","display_name":"Power Line Communications and Noise","score":0.9936000108718872,"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":0.8343747854232788},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7449197173118591},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.7060067653656006},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.6719754934310913},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6149877905845642},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.6084343194961548},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.4661940634250641},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.45907092094421387},{"id":"https://openalex.org/keywords/quality-of-experience","display_name":"Quality of experience","score":0.4265996515750885},{"id":"https://openalex.org/keywords/quality-of-service","display_name":"Quality of service","score":0.38661348819732666},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.34399375319480896},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3396984040737152},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26938679814338684},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13365796208381653}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8343747854232788},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7449197173118591},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.7060067653656006},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.6719754934310913},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6149877905845642},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.6084343194961548},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.4661940634250641},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.45907092094421387},{"id":"https://openalex.org/C2779333187","wikidata":"https://www.wikidata.org/wiki/Q3132648","display_name":"Quality of experience","level":3,"score":0.4265996515750885},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.38661348819732666},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.34399375319480896},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3396984040737152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26938679814338684},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13365796208381653},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tnet.2021.3053771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnet.2021.3053771","pdf_url":null,"source":{"id":"https://openalex.org/S62238642","display_name":"IEEE/ACM Transactions on Networking","issn_l":"1063-6692","issn":["1063-6692","1558-2566"],"is_oa":false,"is_in_doaj":false,"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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Networking","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G969433377","display_name":null,"funder_award_id":"2017GC010465","funder_id":"https://openalex.org/F4320334009","funder_display_name":"Guangdong Provincial Pearl River Talents Program"}],"funders":[{"id":"https://openalex.org/F4320334009","display_name":"Guangdong Provincial Pearl River Talents Program","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1964122966","https://openalex.org/W1979868020","https://openalex.org/W1986620394","https://openalex.org/W2008783708","https://openalex.org/W2009139797","https://openalex.org/W2017957151","https://openalex.org/W2021247827","https://openalex.org/W2024379753","https://openalex.org/W2025490781","https://openalex.org/W2034518457","https://openalex.org/W2045522464","https://openalex.org/W2046269338","https://openalex.org/W2064675550","https://openalex.org/W2087179032","https://openalex.org/W2090180173","https://openalex.org/W2097998348","https://openalex.org/W2110519532","https://openalex.org/W2110838621","https://openalex.org/W2111073013","https://openalex.org/W2121863487","https://openalex.org/W2122658093","https://openalex.org/W2129733867","https://openalex.org/W2137001001","https://openalex.org/W2137983211","https://openalex.org/W2151062451","https://openalex.org/W2165150801","https://openalex.org/W2173248099","https://openalex.org/W2190432600","https://openalex.org/W2261342007","https://openalex.org/W2611847050","https://openalex.org/W2745732999","https://openalex.org/W2767359317","https://openalex.org/W2787753888","https://openalex.org/W2788134583","https://openalex.org/W2788355865","https://openalex.org/W2807900833","https://openalex.org/W2890928364","https://openalex.org/W2963035276","https://openalex.org/W2963124587","https://openalex.org/W2963728120","https://openalex.org/W2963864421","https://openalex.org/W2980856918","https://openalex.org/W3102058818","https://openalex.org/W3104727908","https://openalex.org/W3146803896","https://openalex.org/W4214717370","https://openalex.org/W4302570325","https://openalex.org/W6656779627","https://openalex.org/W6674385629","https://openalex.org/W6679592330","https://openalex.org/W6684205842","https://openalex.org/W6684921986","https://openalex.org/W6687472758","https://openalex.org/W6748555476","https://openalex.org/W6754052697"],"related_works":["https://openalex.org/W2303288554","https://openalex.org/W3033750547","https://openalex.org/W2029216794","https://openalex.org/W4386698331","https://openalex.org/W2047225036","https://openalex.org/W2138314731","https://openalex.org/W2029263917","https://openalex.org/W2093207996","https://openalex.org/W2982446297","https://openalex.org/W2322468729"],"abstract_inverted_index":{"To":[0,59,170,195],"meet":[1],"the":[2,25,32,61,107,124,130,136,150,172,178,197,217,233],"ever":[3],"increasing":[4],"mobile":[5,143,147],"traffic":[6,82,125,148],"demand":[7],"in":[8,18,177],"5G":[9],"era,":[10],"base":[11,75],"stations":[12,76],"(BSs)":[13],"have":[14],"been":[15],"densely":[16],"deployed":[17],"radio":[19],"access":[20],"networks":[21],"(RANs)":[22],"to":[23,39,71,105],"increase":[24],"network":[26],"coverage":[27],"and":[28,116,138],"capacity.":[29],"However,":[30],"as":[31,157],"high":[33],"density":[34],"of":[35,50,64,119,142,174],"BSs":[36,53],"is":[37,70,155,163],"designed":[38],"accommodate":[40],"peak":[41],"traffic,":[42],"it":[43],"would":[44],"consume":[45],"an":[46,67,211],"unnecessarily":[47],"large":[48],"amount":[49],"energy":[51,62,114],"if":[52],"are":[54,127],"on":[55],"during":[56],"off-peak":[57],"time.":[58],"save":[60],"consumption":[63,115],"cellular":[65],"networks,":[66],"effective":[68],"way":[69],"deactivate":[72],"some":[73],"idle":[74],"that":[77,162,187,227],"do":[78],"not":[79],"serve":[80],"any":[81],"demand.":[83],"In":[84],"this":[85],"paper,":[86],"we":[87,181,200],"develop":[88],"a":[89,100,158,183,202,223],"traffic-aware":[90],"dynamic":[91,179],"BS":[92,108,151],"sleep":[93,152],"control":[94,153],"framework,":[95],"named":[96],"DeepBSC,":[97],"which":[98,134,214],"presents":[99],"novel":[101],"data-driven":[102],"learning":[103,168],"approach":[104],"determine":[106],"active/sleep":[109],"modes":[110],"while":[111],"meeting":[112],"lower":[113],"satisfactory":[117],"Quality":[118],"Service":[120],"(QoS)":[121],"requirements.":[122],"Specifically,":[123],"demands":[126],"predicted":[128],"by":[129,165],"proposed":[131,229],"GS-STN":[132],"model,":[133],"leverages":[135],"geographical":[137],"semantic":[139],"spatial-temporal":[140],"correlations":[141],"traffic.":[144],"With":[145],"accurate":[146],"forecasting,":[149],"problem":[154],"cast":[156],"Markov":[159],"Decision":[160],"Process":[161],"solved":[164],"Actor-Critic":[166],"reinforcement":[167],"methods.":[169,235],"reduce":[171],"variance":[173],"cost":[175],"estimation":[176],"environment,":[180],"propose":[182],"benchmark":[184],"transformation":[185],"method":[186],"provides":[188],"robust":[189],"performance":[190],"indicator":[191],"for":[192],"policy":[193],"update.":[194],"expedite":[196],"training":[198],"process,":[199],"adopt":[201],"Deep":[203],"Deterministic":[204],"Policy":[205],"Gradient":[206],"(DDPG)":[207],"approach,":[208],"together":[209],"with":[210,222],"explorer":[212],"network,":[213],"can":[215],"strengthen":[216],"exploration":[218],"further.":[219],"Extensive":[220],"experiments":[221],"real-world":[224],"dataset":[225],"corroborate":[226],"our":[228],"framework":[230],"significantly":[231],"outperforms":[232],"existing":[234]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":37},{"year":2023,"cited_by_count":28},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}