{"id":"https://openalex.org/W2963543042","doi":"https://doi.org/10.1109/icc.2018.8422168","title":"Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks","display_name":"Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2963543042","doi":"https://doi.org/10.1109/icc.2018.8422168","mag":"2963543042"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2018.8422168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2018.8422168","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 (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/A5100696870","display_name":"Yiding Yu","orcid":"https://orcid.org/0000-0002-3538-576X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiding Yu","raw_affiliation_strings":["Department of Information Engineering, The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066110295","display_name":"Taotao Wang","orcid":"https://orcid.org/0000-0001-9454-4997"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Taotao Wang","raw_affiliation_strings":["Department of Information Engineering, The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019164720","display_name":"Soung Chang Liew","orcid":"https://orcid.org/0000-0001-7055-6483"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Soung Chang Liew","raw_affiliation_strings":["Department of Information Engineering, The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100696870"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":6.1801,"has_fulltext":false,"cited_by_count":66,"citation_normalized_percentile":{"value":0.96982666,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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/T11158","display_name":"Wireless Networks and Protocols","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/T10796","display_name":"Cooperative Communication and Network Coding","score":0.9995999932289124,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8172765970230103},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8160693645477295},{"id":"https://openalex.org/keywords/time-division-multiple-access","display_name":"Time division multiple access","score":0.73880934715271},{"id":"https://openalex.org/keywords/aloha","display_name":"Aloha","score":0.712785005569458},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.5677645802497864},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4974069893360138},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.48613640666007996},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.47640931606292725},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.44355452060699463},{"id":"https://openalex.org/keywords/channel-access-method","display_name":"Channel access method","score":0.4361850619316101},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3673303723335266},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.29972437024116516},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.18589061498641968}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8172765970230103},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8160693645477295},{"id":"https://openalex.org/C117313154","wikidata":"https://www.wikidata.org/wiki/Q878344","display_name":"Time division multiple access","level":2,"score":0.73880934715271},{"id":"https://openalex.org/C2776398200","wikidata":"https://www.wikidata.org/wiki/Q508880","display_name":"Aloha","level":4,"score":0.712785005569458},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.5677645802497864},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4974069893360138},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.48613640666007996},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.47640931606292725},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.44355452060699463},{"id":"https://openalex.org/C193430537","wikidata":"https://www.wikidata.org/wiki/Q1665191","display_name":"Channel access method","level":3,"score":0.4361850619316101},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3673303723335266},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.29972437024116516},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.18589061498641968},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc.2018.8422168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2018.8422168","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 (ICC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W1810054459","https://openalex.org/W1976294375","https://openalex.org/W2051376838","https://openalex.org/W2107726111","https://openalex.org/W2121863487","https://openalex.org/W2123927904","https://openalex.org/W2145339207","https://openalex.org/W2147524058","https://openalex.org/W2163905491","https://openalex.org/W2257979135","https://openalex.org/W2612336410","https://openalex.org/W2766701808","https://openalex.org/W2951031964","https://openalex.org/W4214717370","https://openalex.org/W6683851007","https://openalex.org/W6745758726"],"related_works":["https://openalex.org/W1991933460","https://openalex.org/W3011338823","https://openalex.org/W2153998550","https://openalex.org/W1945372791","https://openalex.org/W2156941064","https://openalex.org/W1917444284","https://openalex.org/W2131307709","https://openalex.org/W1567375642","https://openalex.org/W3184466926","https://openalex.org/W2162587296"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"the":[3,11,33,69,78,94,101,120,141,157,163,169,179,193],"use":[4,194],"of":[5,13,35,71,80,103,110,119,135,154,156,195,227],"deep":[6],"reinforcement":[7,204],"learning":[8],"(DRL)":[9],"in":[10,58,166,198,217,229],"design":[12,27,50],"a":[14,38,48,108,152,174],"\"universal\"":[15],"MAC":[16,95,116,121,144,181],"protocol":[17],"referred":[18],"to":[19,44,202,210],"as":[20],"Deep-reinforcement":[21],"Learning":[22],"Multiple":[23],"Access":[24],"(DLMA).":[25],"The":[26,125,132],"framework":[28,172],"is":[29,74,89,123],"partially":[30],"inspired":[31],"by":[32,151],"vision":[34],"DARPA":[36,72],"SC2,":[37],"3-year":[39],"competition":[40],"whereby":[41],"competitors":[42],"are":[43,128,146],"come":[45],"up":[46],"with":[47,55,168,186],"clean-slate":[49],"that":[51,113,140],"\"best":[52],"share":[53],"spectrum":[54],"any":[56,59],"network(s),":[57],"environment,":[60,158],"without":[61],"prior":[62],"knowledge,":[63],"leveraging":[64],"on":[65],"machine-learning":[66],"technique\".":[67],"While":[68],"scope":[70],"SC2":[73],"broad":[75],"and":[76,83,91,130,148,162,188,213],"involves":[77,93],"redesign":[79],"PHY,":[81],"MAC,":[82],"Network":[84],"layers,":[85],"this":[86],"paper's":[87],"focus":[88],"narrower":[90],"only":[92],"design.":[96],"In":[97,191],"particular,":[98,192],"we":[99],"consider":[100],"problem":[102],"sharing":[104],"time":[105],"slots":[106],"among":[107],"multiple":[109],"time-slotted":[111],"networks":[112,197],"adopt":[114],"different":[115],"protocols.":[117],"One":[118],"protocols":[122,145],"DLMA.":[124],"other":[126,142],"two":[127,143,221],"TDMA":[129,147,187],"ALOHA.":[131,149],"DRL":[133,170,175,199],"agents":[134],"DLMA":[136,228],"do":[137],"not":[138],"know":[139],"Yet,":[150],"series":[153],"observations":[155],"its":[159],"own":[160],"actions,":[161],"rewards":[164],"-":[165,173],"accordance":[167],"algorithmic":[171],"agent":[176],"can":[177],"learn":[178],"optimal":[180,211],"strategy":[182],"for":[183,207,224],"harmonious":[184],"co-existence":[185],"ALOHA":[189],"nodes.":[190],"neural":[196],"(as":[200],"opposed":[201],"traditional":[203],"learning)":[205],"allows":[206],"fast":[208],"convergence":[209],"solutions":[212],"robustness":[214],"against":[215],"perturbation":[216],"hyper-":[218],"parameter":[219],"settings,":[220],"essential":[222],"properties":[223],"practical":[225],"deployment":[226],"real":[230],"wireless":[231],"networks.":[232]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":26},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}