{"id":"https://openalex.org/W3132893304","doi":"https://doi.org/10.1109/lcomm.2020.3031195","title":"Extreme Learning Machine-Based Receiver for Multi-User Massive MIMO Systems","display_name":"Extreme Learning Machine-Based Receiver for Multi-User Massive MIMO Systems","publication_year":2020,"publication_date":"2020-10-14","ids":{"openalex":"https://openalex.org/W3132893304","doi":"https://doi.org/10.1109/lcomm.2020.3031195","mag":"3132893304"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2020.3031195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2020.3031195","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-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/A5002308460","display_name":"Diego Fernando Carrera","orcid":"https://orcid.org/0000-0001-9011-1115"},"institutions":[{"id":"https://openalex.org/I98461037","display_name":"Tecnol\u00f3gico de Monterrey","ror":"https://ror.org/03ayjn504","country_code":"MX","type":"education","lineage":["https://openalex.org/I98461037"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Diego Fernando Carrera","raw_affiliation_strings":["School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico"],"raw_orcid":"https://orcid.org/0000-0001-9011-1115","affiliations":[{"raw_affiliation_string":"School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico","institution_ids":["https://openalex.org/I98461037"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020226580","display_name":"David Zabala\u2010Blanco","orcid":"https://orcid.org/0000-0002-5692-5673"},"institutions":[{"id":"https://openalex.org/I2799535320","display_name":"Catholic University of the Maule","ror":"https://ror.org/04vdpck27","country_code":"CL","type":"education","lineage":["https://openalex.org/I2799535320"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"David Zabala-Blanco","raw_affiliation_strings":["Department of Computing Science and Industry, Universidad Cat\u00f3lica del Maule, Talca, Chile"],"raw_orcid":"https://orcid.org/0000-0002-5692-5673","affiliations":[{"raw_affiliation_string":"Department of Computing Science and Industry, Universidad Cat\u00f3lica del Maule, Talca, Chile","institution_ids":["https://openalex.org/I2799535320"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063457306","display_name":"Cesar Vargas\u2010Rosales","orcid":"https://orcid.org/0000-0003-1770-471X"},"institutions":[{"id":"https://openalex.org/I98461037","display_name":"Tecnol\u00f3gico de Monterrey","ror":"https://ror.org/03ayjn504","country_code":"MX","type":"education","lineage":["https://openalex.org/I98461037"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Cesar Vargas-Rosales","raw_affiliation_strings":["School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico"],"raw_orcid":"https://orcid.org/0000-0003-1770-471X","affiliations":[{"raw_affiliation_string":"School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico","institution_ids":["https://openalex.org/I98461037"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043473873","display_name":"C\u00e9sar A. Azurdia-Meza","orcid":"https://orcid.org/0000-0003-3461-4484"},"institutions":[{"id":"https://openalex.org/I69737025","display_name":"University of Chile","ror":"https://ror.org/047gc3g35","country_code":"CL","type":"education","lineage":["https://openalex.org/I69737025"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Cesar A. Azurdia-Meza","raw_affiliation_strings":["Department of Electrical Engineering, Universidad de Chile, Santiago, Chile"],"raw_orcid":"https://orcid.org/0000-0003-3461-4484","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Universidad de Chile, Santiago, Chile","institution_ids":["https://openalex.org/I69737025"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0312,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.89819658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"25","issue":"2","first_page":"484","last_page":"488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.9980999827384949,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9948999881744385,"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/mimo","display_name":"MIMO","score":0.8325194120407104},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.7774213552474976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7011106610298157},{"id":"https://openalex.org/keywords/telecommunications-link","display_name":"Telecommunications link","score":0.6983822584152222},{"id":"https://openalex.org/keywords/bit-error-rate","display_name":"Bit error rate","score":0.5336979627609253},{"id":"https://openalex.org/keywords/spectral-efficiency","display_name":"Spectral efficiency","score":0.48722949624061584},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45883435010910034},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.4312899112701416},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4231828451156616},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3329910635948181},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28659021854400635},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.26294609904289246},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19054684042930603},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.15489012002944946},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.15458199381828308},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14094409346580505},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.09491261839866638}],"concepts":[{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.8325194120407104},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.7774213552474976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7011106610298157},{"id":"https://openalex.org/C138660444","wikidata":"https://www.wikidata.org/wiki/Q5607897","display_name":"Telecommunications link","level":2,"score":0.6983822584152222},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.5336979627609253},{"id":"https://openalex.org/C137246740","wikidata":"https://www.wikidata.org/wiki/Q583970","display_name":"Spectral efficiency","level":3,"score":0.48722949624061584},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45883435010910034},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.4312899112701416},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4231828451156616},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3329910635948181},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28659021854400635},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.26294609904289246},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19054684042930603},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.15489012002944946},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.15458199381828308},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14094409346580505},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.09491261839866638},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2020.3031195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2020.3031195","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7276256682","display_name":null,"funder_award_id":"255387","funder_id":"https://openalex.org/F4320321739","funder_display_name":"Consejo Nacional de Ciencia y Tecnolog\u00eda"}],"funders":[{"id":"https://openalex.org/F4320321739","display_name":"Consejo Nacional de Ciencia y Tecnolog\u00eda","ror":"https://ror.org/059ex5q34"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1839886797","https://openalex.org/W1896298289","https://openalex.org/W1965895201","https://openalex.org/W1971557564","https://openalex.org/W2102669152","https://openalex.org/W2163572752","https://openalex.org/W2206155246","https://openalex.org/W2497232977","https://openalex.org/W2610968021","https://openalex.org/W2900669374","https://openalex.org/W2944933595","https://openalex.org/W2969517048","https://openalex.org/W2979317621","https://openalex.org/W2980032836","https://openalex.org/W2988549429","https://openalex.org/W3016818269","https://openalex.org/W3103072702","https://openalex.org/W3103126557","https://openalex.org/W3106233732"],"related_works":["https://openalex.org/W2601693592","https://openalex.org/W2553710680","https://openalex.org/W2103590590","https://openalex.org/W4311950697","https://openalex.org/W2047006631","https://openalex.org/W2187692743","https://openalex.org/W1498781268","https://openalex.org/W2038230493","https://openalex.org/W2099955065","https://openalex.org/W2144246991"],"abstract_inverted_index":{"An":[0],"extreme":[1],"learning":[2],"machine":[3],"(ELM)-based":[4],"receiver":[5],"for":[6],"multi-user":[7],"massive":[8],"MIMO":[9,28,76],"systems":[10],"is":[11,23],"introduced.":[12],"The":[13],"proposed":[14],"ELM":[15,60],"combining":[16,29],"method,":[17],"defined":[18],"in":[19],"the":[20,32,38,41,54,59,73,79],"complex":[21],"plane,":[22],"designed":[24],"to":[25,31],"directly":[26],"perform":[27],"processing":[30],"received":[33],"uplink":[34],"signals,":[35],"based":[36],"on":[37],"adoption":[39],"of":[40,56],"pilot":[42],"symbols":[43],"as":[44],"training":[45],"data.":[46],"Numerical":[47],"results":[48],"show":[49],"that":[50],"by":[51],"appropriately":[52],"setting":[53],"number":[55],"hidden":[57],"neurons,":[58],"achieves":[61],"higher":[62],"spectral":[63],"efficiency":[64],"and":[65,84],"smaller":[66],"BER,":[67],"with":[68],"fewer":[69],"floating-point":[70],"operations":[71],"than":[72],"conventional":[74],"linear":[75],"receivers,":[77],"namely":[78],"minimum":[80],"mean":[81],"squared":[82],"error":[83],"maximum":[85],"ratio":[86],"receivers.":[87]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}