{"id":"https://openalex.org/W2974683824","doi":"https://doi.org/10.1109/lwc.2019.2941878","title":"Exploiting Channel Correlations for NLOS ToA Localization With Multivariate Gaussian Mixture Models","display_name":"Exploiting Channel Correlations for NLOS ToA Localization With Multivariate Gaussian Mixture Models","publication_year":2019,"publication_date":"2019-09-16","ids":{"openalex":"https://openalex.org/W2974683824","doi":"https://doi.org/10.1109/lwc.2019.2941878","mag":"2974683824"},"language":"en","primary_location":{"id":"doi:10.1109/lwc.2019.2941878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2019.2941878","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Wireless 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/A5103209064","display_name":"Chunhua Geng","orcid":"https://orcid.org/0000-0001-9340-8598"},"institutions":[{"id":"https://openalex.org/I72090969","display_name":"Nokia (United States)","ror":"https://ror.org/038km2573","country_code":"US","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I72090969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunhua Geng","raw_affiliation_strings":["Sensing and Localization Department, Nokia Bell Labs, Murray Hill, USA"],"raw_orcid":"https://orcid.org/0000-0001-9340-8598","affiliations":[{"raw_affiliation_string":"Sensing and Localization Department, Nokia Bell Labs, Murray Hill, USA","institution_ids":["https://openalex.org/I72090969"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015431603","display_name":"Xin Yuan","orcid":"https://orcid.org/0000-0002-8311-7524"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin Yuan","raw_affiliation_strings":["Robotics and Video Systems Department, Nokia Bell Labs, Murray Hill, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics and Video Systems Department, Nokia Bell Labs, Murray Hill, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059595714","display_name":"Howard Huang","orcid":"https://orcid.org/0000-0002-4510-0246"},"institutions":[{"id":"https://openalex.org/I72090969","display_name":"Nokia (United States)","ror":"https://ror.org/038km2573","country_code":"US","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I72090969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Howard Huang","raw_affiliation_strings":["Sensing and Localization Department, Nokia Bell Labs, Murray Hill, USA"],"raw_orcid":"https://orcid.org/0000-0002-4510-0246","affiliations":[{"raw_affiliation_string":"Sensing and Localization Department, Nokia Bell Labs, Murray Hill, USA","institution_ids":["https://openalex.org/I72090969"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.664,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.90527468,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"9","issue":"1","first_page":"70","last_page":"73"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","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/T10326","display_name":"Indoor and Outdoor Localization Technologies","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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9973999857902527,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9908000230789185,"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/non-line-of-sight-propagation","display_name":"Non-line-of-sight propagation","score":0.8991018533706665},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6765382885932922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6398395299911499},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6261230707168579},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5978706479072571},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.5920498967170715},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5580821633338928},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5457139015197754},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5433725118637085},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5417914390563965},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.41582173109054565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36772671341896057},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13851836323738098},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12757927179336548},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.12534865736961365},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12444835901260376}],"concepts":[{"id":"https://openalex.org/C154910267","wikidata":"https://www.wikidata.org/wiki/Q1740982","display_name":"Non-line-of-sight propagation","level":3,"score":0.8991018533706665},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6765382885932922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6398395299911499},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6261230707168579},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5978706479072571},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.5920498967170715},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5580821633338928},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5457139015197754},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5433725118637085},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5417914390563965},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.41582173109054565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36772671341896057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13851836323738098},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12757927179336548},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.12534865736961365},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12444835901260376},{"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/lwc.2019.2941878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2019.2941878","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Wireless Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1979154650","https://openalex.org/W2038946940","https://openalex.org/W2084503286","https://openalex.org/W2088663943","https://openalex.org/W2100123768","https://openalex.org/W2103072081","https://openalex.org/W2115870554","https://openalex.org/W2124216931","https://openalex.org/W2125777976","https://openalex.org/W2155433113","https://openalex.org/W2156668452","https://openalex.org/W2162718622","https://openalex.org/W2163817142","https://openalex.org/W2225156818","https://openalex.org/W2238394037","https://openalex.org/W2586626833","https://openalex.org/W2606152178","https://openalex.org/W2755061881","https://openalex.org/W2776656643","https://openalex.org/W2838371091","https://openalex.org/W3101380508","https://openalex.org/W3103810454","https://openalex.org/W4285719527","https://openalex.org/W6683207880"],"related_works":["https://openalex.org/W2220190985","https://openalex.org/W2346846619","https://openalex.org/W2417295580","https://openalex.org/W4250921637","https://openalex.org/W1840639769","https://openalex.org/W2033612661","https://openalex.org/W2055354074","https://openalex.org/W198767307","https://openalex.org/W4237200122","https://openalex.org/W2014701453"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"we":[3,47],"develop":[4],"a":[5,43,56],"Bayesian":[6,58],"probabilistic":[7,59],"approach":[8,60],"for":[9],"time-of-arrival":[10],"(ToA)":[11],"localization":[12,45],"in":[13],"non-line-of-sight":[14],"(NLOS)":[15],"channels,":[16],"where":[17],"multivariate":[18],"Gaussian":[19],"mixture":[20],"models":[21],"(GMM)":[22],"are":[23],"used":[24],"to":[25],"approximate":[26],"the":[27,36,51,70],"joint":[28],"distribution":[29],"of":[30],"channel":[31,37,67],"bias":[32],"values":[33],"and":[34,69],"harness":[35],"correlations.":[38],"Using":[39],"over-the-air":[40],"measurements":[41],"from":[42],"proprietary":[44],"system,":[46],"numerically":[48],"demonstrate":[49],"that":[50,61],"proposed":[52],"algorithm":[53],"outperforms":[54],"both":[55],"counterpart":[57],"does":[62],"not":[63],"take":[64],"into":[65],"account":[66],"correlations":[68],"well-known":[71],"non-linear":[72],"least":[73],"square":[74],"(NLS)":[75],"optimization":[76],"method.":[77]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
