{"id":"https://openalex.org/W4246919777","doi":"https://doi.org/10.1109/glocom.2014.7417224","title":"To Send or Not to Send - Learning MAC Contention","display_name":"To Send or Not to Send - Learning MAC Contention","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W4246919777","doi":"https://doi.org/10.1109/glocom.2014.7417224"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2014.7417224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2014.7417224","pdf_url":null,"source":{"id":"https://openalex.org/S4363607712","display_name":"2015 IEEE Global Communications Conference (GLOBECOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Global Communications Conference (GLOBECOM)","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/A5087878970","display_name":"SaiDhiraj Amuru","orcid":"https://orcid.org/0000-0002-7171-0849"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"SaiDhiraj Amuru","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Virginia Tech"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Virginia Tech","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057973603","display_name":"Yuanzhang Xiao","orcid":"https://orcid.org/0000-0002-5821-8569"},"institutions":[{"id":"https://openalex.org/I4210100400","display_name":"Northwestern University","ror":"https://ror.org/00m6w7z96","country_code":"PH","type":"education","lineage":["https://openalex.org/I4210100400"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Yuanzhang Xiao","raw_affiliation_strings":["Department of ECE, Northwestern University"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Northwestern University","institution_ids":["https://openalex.org/I4210100400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012339002","display_name":"Mihaela van der Schaar","orcid":"https://orcid.org/0000-0003-3933-6049"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mihaela van der Schaar","raw_affiliation_strings":["Department of Electrical Engineering, UCLA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, UCLA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090401828","display_name":"R. Michael Buehrer","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Michael Buehrer","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Virginia Tech"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Virginia Tech","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087878970"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.43563766,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11158","display_name":"Wireless Networks and Protocols","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11158","display_name":"Wireless Networks and Protocols","score":1.0,"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/T11409","display_name":"Advanced Wireless Network Optimization","score":0.9955000281333923,"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/T10246","display_name":"Mobile Ad Hoc Networks","score":0.9860000014305115,"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":0.8496005535125732},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.7076008319854736},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.5577088594436646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5383087396621704},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5288774967193604},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5258595943450928},{"id":"https://openalex.org/keywords/instance-based-learning","display_name":"Instance-based learning","score":0.49601849913597107},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.48237815499305725},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.468168705701828},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4478326439857483},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.36014923453330994},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.34106385707855225}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8496005535125732},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.7076008319854736},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.5577088594436646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5383087396621704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5288774967193604},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5258595943450928},{"id":"https://openalex.org/C24138899","wikidata":"https://www.wikidata.org/wiki/Q17141258","display_name":"Instance-based learning","level":3,"score":0.49601849913597107},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.48237815499305725},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.468168705701828},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4478326439857483},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.36014923453330994},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.34106385707855225},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/glocom.2014.7417224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2014.7417224","pdf_url":null,"source":{"id":"https://openalex.org/S4363607712","display_name":"2015 IEEE Global Communications Conference (GLOBECOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W18936547","https://openalex.org/W90489852","https://openalex.org/W1499245237","https://openalex.org/W1586023924","https://openalex.org/W1966626803","https://openalex.org/W1984564177","https://openalex.org/W2007316963","https://openalex.org/W2096346473","https://openalex.org/W2110621360","https://openalex.org/W2128435715","https://openalex.org/W2138717292","https://openalex.org/W2145101515","https://openalex.org/W2150196105","https://openalex.org/W2160794420","https://openalex.org/W2162598825","https://openalex.org/W2165745152","https://openalex.org/W2167024399","https://openalex.org/W2172021834","https://openalex.org/W2964273152","https://openalex.org/W6600750447","https://openalex.org/W6681968757","https://openalex.org/W6683532021"],"related_works":["https://openalex.org/W2808418668","https://openalex.org/W2357975469","https://openalex.org/W2101748387","https://openalex.org/W3096874164","https://openalex.org/W4281812492","https://openalex.org/W2315999538","https://openalex.org/W3105579180","https://openalex.org/W2970347269","https://openalex.org/W3167472281","https://openalex.org/W4400868993"],"abstract_inverted_index":{"The":[0],"exponential":[1],"back-off":[2,23,52,68],"mechanism,":[3],"proposed":[4,122,178],"for":[5,156],"reducing":[6],"MAC-":[7],"layer":[8],"contention":[9],"in":[10,16,144,194,226],"the":[11,19,47,66,75,81,91,94,110,118,121,134,154,162,174,177,187,213,221,229,233],"802.11":[12,96],"standard,":[13],"is":[14],"sub-optimal":[15],"terms":[17,195],"of":[18,49,80,120,165,176,196,232],"network":[20],"throughput.":[21],"This":[22],"mechanism":[24,53],"and":[25,39,59,150,182,192,198,210,216],"its":[26],"improved":[27],"variants":[28],"are":[29,88,126,235],"especially":[30,225],"inefficient":[31],"under":[32,70],"unknown":[33,71],"dynamics":[34,83],"such":[35],"as":[36,54,85,170],"packet":[37],"arrivals":[38],"user":[40],"entry/exit.":[41],"In":[42],"this":[43,51,204],"paper,":[44],"we":[45,98],"formulate":[46],"problem":[48,205],"optimizing":[50],"a":[55,100,207],"Markov":[56],"decision":[57],"process,":[58],"propose":[60,99],"online":[61,123],"learning":[62,105,111,124,148,163,167,180,223],"algorithms":[63,168],"to":[64,107,114,141,146],"learn":[65],"optimal":[67],"schemes":[69],"dynamics.":[72],"By":[73],"exploiting":[74],"fact":[76],"that":[77,127,137],"some":[78],"components":[79],"system":[82,135],"(such":[84,169],"protocol":[86],"states)":[87],"known":[89],"because":[90],"users":[92,234],"follow":[93],"common":[95],"protocol,":[97],"post-decision":[101],"state":[102],"(PDS)-":[103],"based":[104],"algorithm":[106,125,181],"speed":[108],"up":[109],"process.":[112],"Compared":[113],"traditional":[115],"Q-learning":[116,193],"algorithms,":[117,149],"advantages":[119],"1)":[128],"it":[129,152],"exploits":[130],"partial":[131],"information":[132,139],"about":[133],"so":[136],"less":[138],"needs":[140],"be":[142],"learned":[143],"comparison":[145],"other":[147],"2)":[151],"removes":[153],"necessity":[155],"action":[157],"exploration":[158],"which":[159],"usually":[160],"impedes":[161],"process":[164],"conventional":[166],"Q-Learning).":[171],"We":[172,201],"prove":[173],"optimality":[175],"PDS-based":[179],"via":[183],"numerical":[184],"results":[185],"demonstrate":[186],"improvement":[188],"over":[189],"existing":[190],"protocols":[191],"throughput":[197],"convergence":[199],"speed.":[200],"first":[202],"address":[203],"from":[206],"single-user":[208],"perspective":[209],"later":[211],"describe":[212],"challenges":[214],"involved":[215],"present":[217],"new":[218],"insights":[219],"into":[220],"multi-user":[222],"scenarios,":[224],"cases":[227],"where":[228],"MDP":[230],"models":[231],"coupled":[236],"with":[237],"each":[238],"other.":[239]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
