{"id":"https://openalex.org/W3200357587","doi":"https://doi.org/10.1109/icufn49451.2021.9528565","title":"Deep Learning-based Power Allocation in Massive MIMO Systems with SLNR and SINR Criterions","display_name":"Deep Learning-based Power Allocation in Massive MIMO Systems with SLNR and SINR Criterions","publication_year":2021,"publication_date":"2021-08-17","ids":{"openalex":"https://openalex.org/W3200357587","doi":"https://doi.org/10.1109/icufn49451.2021.9528565","mag":"3200357587"},"language":"en","primary_location":{"id":"doi:10.1109/icufn49451.2021.9528565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icufn49451.2021.9528565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN)","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/A5042167303","display_name":"Ridho Hendra Yoga Perdana","orcid":"https://orcid.org/0000-0002-1680-1190"},"institutions":[{"id":"https://openalex.org/I94588446","display_name":"Hongik University","ror":"https://ror.org/00egdv862","country_code":"KR","type":"education","lineage":["https://openalex.org/I94588446"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Ridho Hendra Yoga Perdana","raw_affiliation_strings":["Graduate School, Hongik University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Graduate School, Hongik University, Republic of Korea","institution_ids":["https://openalex.org/I94588446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021007706","display_name":"Toan-Van Nguyen","orcid":"https://orcid.org/0000-0002-1968-8170"},"institutions":[{"id":"https://openalex.org/I94588446","display_name":"Hongik University","ror":"https://ror.org/00egdv862","country_code":"KR","type":"education","lineage":["https://openalex.org/I94588446"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Toan-Van Nguyen","raw_affiliation_strings":["Graduate School, Hongik University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Graduate School, Hongik University, Republic of Korea","institution_ids":["https://openalex.org/I94588446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037079266","display_name":"Beongku An","orcid":"https://orcid.org/0000-0002-0587-3754"},"institutions":[{"id":"https://openalex.org/I94588446","display_name":"Hongik University","ror":"https://ror.org/00egdv862","country_code":"KR","type":"education","lineage":["https://openalex.org/I94588446"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Beongku An","raw_affiliation_strings":["Hongik University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Hongik University, Republic of Korea","institution_ids":["https://openalex.org/I94588446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042167303"],"corresponding_institution_ids":["https://openalex.org/I94588446"],"apc_list":null,"apc_paid":null,"fwci":1.0027,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.75731139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"87","last_page":"92"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":1.0,"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":1.0,"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":0.9988999962806702,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9979000091552734,"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/computer-science","display_name":"Computer science","score":0.7186051607131958},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5553104281425476},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.48209598660469055},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.477610319852829},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.41889074444770813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3757449686527252},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.2775578796863556},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10370835661888123},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09759238362312317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7186051607131958},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5553104281425476},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.48209598660469055},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.477610319852829},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.41889074444770813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3757449686527252},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.2775578796863556},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10370835661888123},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09759238362312317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icufn49451.2021.9528565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icufn49451.2021.9528565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1518945650","https://openalex.org/W1983736000","https://openalex.org/W2037941803","https://openalex.org/W2147601077","https://openalex.org/W2545343974","https://openalex.org/W2560048027","https://openalex.org/W2610968021","https://openalex.org/W2616867685","https://openalex.org/W2761698003","https://openalex.org/W2770606349","https://openalex.org/W2796194003","https://openalex.org/W2885828982","https://openalex.org/W2921224230","https://openalex.org/W2963101290","https://openalex.org/W3010079658","https://openalex.org/W3025048143","https://openalex.org/W3040147542","https://openalex.org/W3101119440","https://openalex.org/W3106233732","https://openalex.org/W3118962670","https://openalex.org/W3132464134","https://openalex.org/W3161785019"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"In":[0,18],"this":[1,73],"paper,":[2],"we":[3,20],"design":[4,144],"a":[5,77,157,161],"deep":[6,81,94,114,142,176],"learning":[7,115,143,177],"framework":[8,78],"for":[9,39,131,191,197],"the":[10,22,53,85,93,103,109,119,123,127,132,137,141,148,152,168,172,192,198],"power":[11,26,54,105,129,153,181],"allocation":[12,27,55,106,130,154,182],"problems":[13,28],"in":[14,125,179],"massive":[15],"MIMO":[16],"networks.":[17],"particular,":[19],"formulate":[21],"max-min":[23,193],"and":[24,34,96,195],"max-product":[25,199],"by":[29,75],"using":[30],"signal-to-interference-plus-noise":[31],"ratio":[32,36],"(SINR)":[33],"signal-to-leak-plus-noise":[35],"(SLNR)":[37],"criteria":[38],"linear":[40],"precoder":[41],"design.":[42],"Multiple":[43],"base":[44],"stations":[45],"are":[46],"deployed":[47],"to":[48,57,65,91,101,108,117,136,146],"serve":[49],"multiple":[50],"user":[51,59,86,133],"equipments,":[52],"process":[56],"each":[58],"equipment":[60,87],"takes":[61],"long":[62],"processing":[63,120],"time":[64,121,159],"converge,":[66],"which":[67],"is":[68,89,99],"inefficient":[69],"approach.":[70],"We":[71],"tackle":[72],"problem":[74,155],"designing":[76],"based":[79],"on":[80],"neural":[82],"network,":[83],"where":[84],"position":[88],"used":[90,100],"train":[92],"model,":[95],"then":[97],"it":[98],"predict":[102],"optimal":[104,128,149],"according":[107],"user's":[110],"locations.":[111],"The":[112],"resulting":[113],"helps":[116,145],"reduce":[118],"of":[122,151,189],"system":[124],"determining":[126],"equipment.":[134],"Compared":[135],"standard":[138],"optimization":[139],"approach,":[140],"obtain":[147],"solution":[150],"within":[156],"short":[158],"via":[160],"quick-inference":[162],"process.":[163],"Simulation":[164],"results":[165,185],"show":[166],"that":[167],"SINR":[169],"criterion":[170],"outperforms":[171],"SLNR":[173],"one.":[174],"Meanwhile,":[175],"performance":[178],"predicting":[180],"gets":[183],"excellent":[184],"with":[186],"an":[187],"accuracy":[188],"85%":[190],"strategy":[194],"99%":[196],"strategy.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}