{"id":"https://openalex.org/W4405103850","doi":"https://doi.org/10.1109/milcom61039.2024.10773886","title":"Semi-decentralized Message Allocation for Cell-Free Networks using Unsupervised Learning","display_name":"Semi-decentralized Message Allocation for Cell-Free Networks using Unsupervised Learning","publication_year":2024,"publication_date":"2024-10-28","ids":{"openalex":"https://openalex.org/W4405103850","doi":"https://doi.org/10.1109/milcom61039.2024.10773886"},"language":"en","primary_location":{"id":"doi:10.1109/milcom61039.2024.10773886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/milcom61039.2024.10773886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MILCOM 2024 - 2024 IEEE Military Communications Conference (MILCOM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5020893489","display_name":"Noel Teku","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Noel Teku","raw_affiliation_strings":["University of Arizona,Department of Electrical and Computer Engineering,Tucson,Arizona,85719"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Arizona,Department of Electrical and Computer Engineering,Tucson,Arizona,85719","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004316408","display_name":"Ravi Tandon","orcid":"https://orcid.org/0000-0002-6182-6098"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravi Tandon","raw_affiliation_strings":["University of Arizona,Department of Electrical and Computer Engineering,Tucson,Arizona,85719"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Arizona,Department of Electrical and Computer Engineering,Tucson,Arizona,85719","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045154295","display_name":"Tamal Bose","orcid":"https://orcid.org/0000-0001-7743-0832"},"institutions":[{"id":"https://openalex.org/I4210149348","display_name":"EpiSys Science (United States)","ror":"https://ror.org/04k8txf58","country_code":"US","type":"company","lineage":["https://openalex.org/I4210149348"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tamal Bose","raw_affiliation_strings":["EpiSci,Poway,California,92064"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EpiSci,Poway,California,92064","institution_ids":["https://openalex.org/I4210149348"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"554","last_page":"559"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10796","display_name":"Cooperative Communication and Network Coding","score":0.9972000122070312,"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/T10796","display_name":"Cooperative Communication and Network Coding","score":0.9972000122070312,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.996399998664856,"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/T10575","display_name":"Wireless Communication Networks Research","score":0.9958000183105469,"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":0.7216008901596069},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4236336052417755},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.37751758098602295},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.35420989990234375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3036912977695465}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7216008901596069},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4236336052417755},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.37751758098602295},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35420989990234375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3036912977695465}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/milcom61039.2024.10773886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/milcom61039.2024.10773886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MILCOM 2024 - 2024 IEEE Military Communications Conference (MILCOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320332359","display_name":"Office of Science","ror":"https://ror.org/00mmn6b08"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1985928509","https://openalex.org/W2115490553","https://openalex.org/W2286275639","https://openalex.org/W2797535556","https://openalex.org/W2920437197","https://openalex.org/W2964042011","https://openalex.org/W2974046131","https://openalex.org/W3036275239","https://openalex.org/W3080441795","https://openalex.org/W3158832185","https://openalex.org/W3159657576","https://openalex.org/W3183478447","https://openalex.org/W3215078284","https://openalex.org/W4226227183","https://openalex.org/W4290996277","https://openalex.org/W4312589951","https://openalex.org/W4315630131","https://openalex.org/W4382677748"],"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":{"In":[0,84],"this":[1,85],"paper,":[2,86],"we":[3,87],"present":[4],"an":[5],"unsupervised":[6],"learning":[7,94,230],"framework":[8,96],"for":[9,16,65,97,158,177],"message":[10,56,66,98,156,220],"allocation":[11,57,67,221,249],"in":[12,39],"Cell-free":[13],"networks":[14],"(CFNs)":[15],"latency":[17,141,150,187,198],"minimization.":[18],"One":[19],"of":[20,24,55,73,138,142,165,184,197,237],"the":[21,53,70,74,130,136,140,143,148,153,162,166,171,179,186,192,200,227,235,238],"key":[22,201],"features":[23],"CFNs":[25],"is":[26,133,161,188],"that":[27,226],"users\u2019":[28],"data":[29],"can":[30,68,233],"be":[31],"decoded":[32],"by":[33,43,181],"multiple":[34,48],"access":[35],"points":[36],"(APs),":[37],"i.e.,":[38],"a":[40,61,90,109,113,120],"\"cell-free\"":[41],"manner":[42],"letting":[44],"users":[45],"connect":[46],"to":[47,52,104,169],"APs":[49],"simultaneously;":[50],"leading":[51],"problem":[54],"across":[58],"APs.":[59],"While":[60],"fully":[62],"centralized":[63,212,239],"approach":[64,209,234],"make":[69],"most":[71],"out":[72],"flexibility":[75],"offered":[76],"via":[77],"CFNs,":[78],"it":[79],"requires":[80],"prohibitive":[81],"coordination":[82,244],"overhead.":[83],"instead":[88],"propose":[89],"novel":[91],"semi-decentralized":[92,208,228],"machine":[93,229],"based":[95,231],"allocation.":[99],"It":[100],"allows":[101],"each":[102,159],"user":[103,160],"split":[105,157],"their":[106],"messages":[107],"using":[108],"\"learned\"":[110],"model":[111,132,180],"(e.g.,":[112],"neural":[114],"network)":[115],"which":[116],"takes":[117],"two":[118],"inputs:":[119],"user\u2019s":[121],"local":[122],"channel":[123],"gains":[124],"and":[125,204,218,246],"aggregate":[126],"global":[127],"SINRs":[128],"at":[129],"APs.The":[131],"trained":[134],"with":[135,241],"objective":[137],"minimizing":[139],"network.":[144],"To":[145],"accomplish":[146],"this,":[147],"total":[149],"derived":[151],"from":[152],"model\u2019s":[154],"learned":[155],"main":[163],"component":[164],"loss":[167],"used":[168],"update":[170],"model.":[172],"Different":[173],"methods":[174,213,240],"are":[175],"investigated":[176],"training":[178],"presenting":[182],"variations":[183],"how":[185],"computed.":[189],"We":[190],"use":[191],"cumulative":[193],"distribution":[194],"function":[195],"(CDF)":[196],"as":[199,214,216],"performance":[202,236],"metric":[203],"compare":[205],"our":[206],"proposed":[207],"against":[210],"several":[211],"well":[215],"uniform":[217],"greedy":[219],"techniques.":[222],"Our":[223],"results":[224],"indicate":[225],"method":[232],"very":[242],"little":[243],"overhead":[245],"outperforms":[247],"greedy/uniform":[248],"methods.":[250]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
