{"id":"https://openalex.org/W4200031447","doi":"https://doi.org/10.23919/cnsm52442.2021.9615550","title":"Reinforcement Learning for Automated Energy Efficient Mobile Network Performance Tuning","display_name":"Reinforcement Learning for Automated Energy Efficient Mobile Network Performance Tuning","publication_year":2021,"publication_date":"2021-10-25","ids":{"openalex":"https://openalex.org/W4200031447","doi":"https://doi.org/10.23919/cnsm52442.2021.9615550"},"language":"en","primary_location":{"id":"doi:10.23919/cnsm52442.2021.9615550","is_oa":false,"landing_page_url":"https://doi.org/10.23919/cnsm52442.2021.9615550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th International Conference on Network and Service Management (CNSM)","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/A5064149370","display_name":"Diarmuid Corcoran","orcid":null},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]},{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Diarmuid Corcoran","raw_affiliation_strings":["Ericsson AB and Software and Computer Systems, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"Ericsson AB and Software and Computer Systems, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016","https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064297162","display_name":"Per Kreuger","orcid":"https://orcid.org/0000-0002-9331-0352"},"institutions":[{"id":"https://openalex.org/I2800664555","display_name":"RISE Research Institutes of Sweden","ror":"https://ror.org/03nnxqz81","country_code":"SE","type":"other","lineage":["https://openalex.org/I2800664555"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Per Kreuger","raw_affiliation_strings":["RISE AI Research Institutes of Sweden, Kista, Sweden"],"affiliations":[{"raw_affiliation_string":"RISE AI Research Institutes of Sweden, Kista, Sweden","institution_ids":["https://openalex.org/I2800664555"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021753785","display_name":"Magnus Boman","orcid":"https://orcid.org/0000-0001-7949-1815"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Magnus Boman","raw_affiliation_strings":["Software and Computer Systems, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"Software and Computer Systems, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5064149370"],"corresponding_institution_ids":["https://openalex.org/I1306339040","https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.3008,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57613237,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"216","last_page":"224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9998999834060669,"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":0.9998999834060669,"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/T11392","display_name":"Energy Harvesting in Wireless Networks","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/T11409","display_name":"Advanced Wireless Network Optimization","score":0.9987999796867371,"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":0.8649850487709045},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8242655992507935},{"id":"https://openalex.org/keywords/interleaving","display_name":"Interleaving","score":0.7264847159385681},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5344181656837463},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5088837146759033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3900630474090576},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34581106901168823},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11318734288215637}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8649850487709045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8242655992507935},{"id":"https://openalex.org/C28034677","wikidata":"https://www.wikidata.org/wiki/Q17092530","display_name":"Interleaving","level":2,"score":0.7264847159385681},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5344181656837463},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5088837146759033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3900630474090576},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34581106901168823},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11318734288215637},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/cnsm52442.2021.9615550","is_oa":false,"landing_page_url":"https://doi.org/10.23919/cnsm52442.2021.9615550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th International Conference on Network and Service Management (CNSM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1600787307","https://openalex.org/W1963533680","https://openalex.org/W1977655452","https://openalex.org/W1986226687","https://openalex.org/W2020081405","https://openalex.org/W2050884147","https://openalex.org/W2061914652","https://openalex.org/W2074128438","https://openalex.org/W2079161532","https://openalex.org/W2099459323","https://openalex.org/W2116485279","https://openalex.org/W2119870041","https://openalex.org/W2148231389","https://openalex.org/W2152927032","https://openalex.org/W2154782861","https://openalex.org/W2155027007","https://openalex.org/W2160160578","https://openalex.org/W2169767092","https://openalex.org/W2274600483","https://openalex.org/W2626514082","https://openalex.org/W2766447205","https://openalex.org/W2783159556","https://openalex.org/W2783589695","https://openalex.org/W2784277076","https://openalex.org/W2890141553","https://openalex.org/W2904934387","https://openalex.org/W2963241379","https://openalex.org/W2966860555","https://openalex.org/W3023012063","https://openalex.org/W3027146252","https://openalex.org/W3033649961","https://openalex.org/W3099782894","https://openalex.org/W3151595784","https://openalex.org/W3161963243","https://openalex.org/W4288091680","https://openalex.org/W4295312788","https://openalex.org/W4298857966","https://openalex.org/W6635760495","https://openalex.org/W6637967152","https://openalex.org/W6683204974","https://openalex.org/W6754447547","https://openalex.org/W6766978945","https://openalex.org/W6773718218","https://openalex.org/W6959881526"],"related_works":["https://openalex.org/W1655266410","https://openalex.org/W2389051085","https://openalex.org/W1901012776","https://openalex.org/W2463883322","https://openalex.org/W2330343234","https://openalex.org/W2814468324","https://openalex.org/W2229382548","https://openalex.org/W2391789612","https://openalex.org/W2389236462","https://openalex.org/W1614034078"],"abstract_inverted_index":{"Modern":[0],"mobile":[1],"networks":[2],"are":[3],"increasingly":[4],"complex":[5,99],"from":[6],"a":[7,57,73,93,161,174,178,188],"resource":[8,104],"management":[9],"perspective,":[10],"with":[11,154],"diverse":[12],"combinations":[13],"of":[14,47,67,88,102,117],"software,":[15],"infrastructure":[16],"elements":[17],"and":[18,25,29,44,75,97,109,134,164],"services":[19],"that":[20,40,123,168],"need":[21],"to":[22,71,79,95,113,132,142,151,172,187],"be":[23,170],"configured":[24],"tuned":[26],"for":[27,191],"correct":[28],"efficient":[30,43],"operation.":[31],"It":[32],"is":[33,56,64,185],"well":[34],"accepted":[35],"in":[36,107,111,144,177],"the":[37,65,86,115,136,183],"communications":[38],"community":[39],"appropriately":[41],"dimensioned,":[42],"reliable":[45],"configurations":[46],"systems":[48],"like":[49],"5G":[50],"or":[51],"indeed":[52],"its":[53],"predecessor":[54],"4G":[55,108],"massive":[58],"technical":[59],"challenge.":[60],"One":[61],"promising":[62],"avenue":[63],"application":[66],"machine":[68],"learning":[69,77,91,149,166],"methods":[70],"apply":[72,98],"data-driven":[74],"continuous":[76,165,192],"approach":[78,167],"automated":[80],"system":[81,138,156,190],"performance":[82],"tuning.":[83],"We":[84,121,158],"demonstrate":[85],"effectiveness":[87],"policy-gradient":[89],"reinforcement":[90],"as":[92],"way":[94],"learn":[96],"interleaving":[100],"patterns":[101],"radio":[103],"block":[105],"usage":[106],"5G,":[110],"order":[112],"automate":[114],"reduction":[116],"cell":[118],"edge":[119],"interference.":[120],"show":[122],"our":[124],"method":[125],"can":[126,169],"increase":[127,135],"overall":[128,137],"spectral":[129],"efficiency":[130,140],"up":[131,141],"25%":[133],"energy":[139],"50%":[143],"very":[145],"challenging":[146],"scenarios":[147],"by":[148],"how":[150],"do":[152],"more":[153],"less":[155],"resources.":[157],"also":[159],"introduce":[160],"flexible":[162],"phased":[163],"used":[171],"train":[173],"bootstrap":[175],"model":[176,184],"simulated":[179],"environment":[180],"after":[181],"which":[182],"transferred":[186],"live":[189],"contextual":[193],"learning.":[194]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
