{"id":"https://openalex.org/W4386066433","doi":"https://doi.org/10.1109/isit54713.2023.10206828","title":"Neural Estimation of Multi-User Capacity Regions","display_name":"Neural Estimation of Multi-User Capacity Regions","publication_year":2023,"publication_date":"2023-06-25","ids":{"openalex":"https://openalex.org/W4386066433","doi":"https://doi.org/10.1109/isit54713.2023.10206828"},"language":"en","primary_location":{"id":"doi:10.1109/isit54713.2023.10206828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit54713.2023.10206828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on Information Theory (ISIT)","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/A5034792810","display_name":"Bashar Huleihel","orcid":"https://orcid.org/0000-0001-9962-2384"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bashar Huleihel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077599107","display_name":"Dor Tsur","orcid":"https://orcid.org/0000-0002-6561-4965"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dor Tsur","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016277732","display_name":"Ziv Aharoni","orcid":"https://orcid.org/0000-0003-0204-4034"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziv Aharoni","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087127628","display_name":"Oron Sabag","orcid":"https://orcid.org/0000-0002-7907-1463"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oron Sabag","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068879871","display_name":"Haim H. Permuter","orcid":"https://orcid.org/0000-0003-3170-3190"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haim H. Permuter","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5034792810"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5294,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.64779279,"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":"2380","last_page":"2385"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9994999766349792,"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":0.9994999766349792,"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/T10860","display_name":"Speech and Audio Processing","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7664599418640137},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7246360778808594},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.6353479623794556},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5647073984146118},{"id":"https://openalex.org/keywords/channel-capacity","display_name":"Channel capacity","score":0.5400058031082153},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5241760611534119},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4475645124912262},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.44348037242889404},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4223178029060364},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3410072922706604},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32666927576065063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2806127071380615},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14201274514198303},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11357364058494568},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10289239883422852}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7664599418640137},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7246360778808594},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.6353479623794556},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5647073984146118},{"id":"https://openalex.org/C97744766","wikidata":"https://www.wikidata.org/wiki/Q870845","display_name":"Channel capacity","level":3,"score":0.5400058031082153},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5241760611534119},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4475645124912262},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.44348037242889404},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4223178029060364},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3410072922706604},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32666927576065063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2806127071380615},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14201274514198303},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11357364058494568},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10289239883422852},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit54713.2023.10206828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit54713.2023.10206828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on Information Theory (ISIT)","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":20,"referenced_works":["https://openalex.org/W1592482298","https://openalex.org/W1965665804","https://openalex.org/W2017970192","https://openalex.org/W2077129893","https://openalex.org/W2122195511","https://openalex.org/W2138437486","https://openalex.org/W2140911775","https://openalex.org/W2147869661","https://openalex.org/W2153105294","https://openalex.org/W2157875630","https://openalex.org/W2160481173","https://openalex.org/W2162935207","https://openalex.org/W2164356790","https://openalex.org/W2296441616","https://openalex.org/W3198016044","https://openalex.org/W4232613155","https://openalex.org/W4327643775","https://openalex.org/W4362654888","https://openalex.org/W6635532581","https://openalex.org/W6681130209"],"related_works":["https://openalex.org/W2051058708","https://openalex.org/W154868527","https://openalex.org/W1494268238","https://openalex.org/W1983207144","https://openalex.org/W2490706771","https://openalex.org/W1976468483","https://openalex.org/W2480116122","https://openalex.org/W1516574938","https://openalex.org/W2563912921","https://openalex.org/W2407611282"],"abstract_inverted_index":{"In":[0,53],"this":[1],"paper,":[2],"we":[3,131],"introduce":[4],"a":[5,23,145,180],"data-driven":[6],"methodology":[7,95,168],"for":[8,171],"estimating":[9],"capacity":[10,20,41,77,123,128],"regions":[11,21,42],"of":[12,46,64,83,93,102,189,197,204],"continuous":[13],"channels":[14],"in":[15,29,62],"multi-user":[16],"communication":[17,31],"systems.":[18],"Computing":[19],"is":[22,35,165,169,177,208],"long":[24],"standing":[25],"open":[26],"problem,":[27],"even":[28],"simple":[30],"scenarios.":[32],"Nevertheless,":[33],"it":[34],"often":[36],"possible":[37],"to":[38,75,111,120],"represent":[39],"their":[40],"as":[43,179],"the":[44,80,84,113,121,127,133,137,157,172,175,183,198,215,220],"limit":[45],"an":[47,152],"optimization":[48],"problem":[49],"(a":[50],"multi-letter":[51,57],"expression).":[52],"many":[54],"cases,":[55],"these":[56,109],"expressions":[58],"can":[59,185],"be":[60],"expressed":[61],"terms":[63,116],"directed":[65,85],"information":[66,86],"(DI)":[67],"rates.":[68],"Accordingly,":[69],"our":[70,94,205],"approach":[71],"utilizes":[72],"neural":[73,87,146],"networks":[74],"estimate":[76,112,126],"regions,":[78],"leveraging":[79],"recent":[81],"introduction":[82],"estimator":[88],"(DINE).":[89],"The":[90,167,202],"main":[91],"idea":[92],"involves":[96],"training":[97],"DINE-based":[98,161],"models":[99,110,159,162],"using":[100,108],"samples":[101],"channel":[103,176,200,218,224],"inputs":[104,191],"and":[105,107,150,160,182,192,219,226],"outputs,":[106,193],"DI":[114,134],"rate":[115],"that":[117],"are":[118,142],"intrinsic":[119],"studied":[122],"region.":[124],"To":[125],"region":[129],"rates,":[130],"optimize":[132],"rates":[135],"over":[136],"involved":[138],"input":[139],"distributions":[140],"which":[141],"parameterized":[143],"by":[144],"distribution":[147],"transformer":[148],"(NDT),":[149],"execute":[151],"alternating":[153],"maximization":[154],"procedure":[155],"between":[156],"NDT":[158],"until":[163],"convergence":[164],"achieved.":[166],"suitable":[170],"case":[173],"where":[174],"treated":[178],"\"black-box\"":[181],"designer":[184],"only":[186],"gather":[187],"observations":[188],"its":[190],"lacking":[194],"any":[195],"knowledge":[196],"explicit":[199],"model.":[201],"performance":[203],"proposed":[206],"algorithm":[207],"shown":[209],"via":[210],"several":[211],"well-known":[212],"settings,":[213],"including":[214],"Gaussian":[216,222],"two-way":[217],"two-user":[221],"multiple-access":[223],"with":[225],"without":[227],"feedback.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2025-10-10T00:00:00"}