{"id":"https://openalex.org/W2936831134","doi":"https://doi.org/10.1109/vtcfall.2018.8690911","title":"Drive Test Minimization Using Deep Learning with Bayesian Approximation","display_name":"Drive Test Minimization Using Deep Learning with Bayesian Approximation","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2936831134","doi":"https://doi.org/10.1109/vtcfall.2018.8690911","mag":"2936831134"},"language":"en","primary_location":{"id":"doi:10.1109/vtcfall.2018.8690911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcfall.2018.8690911","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 88th Vehicular Technology Conference (VTC-Fall)","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/A5023087733","display_name":"Jakob Thrane","orcid":"https://orcid.org/0000-0003-0056-4503"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Jakob Thrane","raw_affiliation_strings":["Department of Photonics Engineering, (DTU Fotonik), Technical University of Denmark, (DTU), Kgs. Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Photonics Engineering, (DTU Fotonik), Technical University of Denmark, (DTU), Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004333570","display_name":"Matteo Artuso","orcid":"https://orcid.org/0000-0003-4572-9535"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Matteo Artuso","raw_affiliation_strings":["Department of Photonics Engineering, (DTU Fotonik), Technical University of Denmark, (DTU), Kgs. Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Photonics Engineering, (DTU Fotonik), Technical University of Denmark, (DTU), Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025311119","display_name":"Darko Zibar","orcid":"https://orcid.org/0000-0003-4182-7488"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Darko Zibar","raw_affiliation_strings":["Department of Photonics Engineering, (DTU Fotonik), Technical University of Denmark, (DTU), Kgs. Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Photonics Engineering, (DTU Fotonik), Technical University of Denmark, (DTU), Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069309470","display_name":"Henrik Lehrmann Christiansen","orcid":"https://orcid.org/0000-0002-9558-3493"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Henrik L. Christiansen","raw_affiliation_strings":["Department of Photonics Engineering, (DTU Fotonik), Technical University of Denmark, (DTU), Kgs. Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Photonics Engineering, (DTU Fotonik), Technical University of Denmark, (DTU), Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023087733"],"corresponding_institution_ids":["https://openalex.org/I96673099"],"apc_list":null,"apc_paid":null,"fwci":1.1772,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.80831371,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9965999722480774,"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":0.9965999722480774,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9908999800682068,"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.7941574454307556},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.712469220161438},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.5403021574020386},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5262207984924316},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5077992081642151},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5057129859924316},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4966621994972229},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.4942665100097656},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4657483994960785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45937690138816833},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.44883933663368225},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3497372269630432},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.14221462607383728},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10941839218139648}],"concepts":[{"id":"https://openalex.org/C154910267","wikidata":"https://www.wikidata.org/wiki/Q1740982","display_name":"Non-line-of-sight propagation","level":3,"score":0.7941574454307556},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.712469220161438},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.5403021574020386},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5262207984924316},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5077992081642151},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5057129859924316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4966621994972229},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.4942665100097656},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4657483994960785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45937690138816833},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.44883933663368225},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3497372269630432},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.14221462607383728},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10941839218139648},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/vtcfall.2018.8690911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcfall.2018.8690911","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 88th Vehicular Technology Conference (VTC-Fall)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/42629c9f-f354-4fa9-b5bc-5a516e76343a","is_oa":false,"landing_page_url":"https://orbit.dtu.dk/en/publications/42629c9f-f354-4fa9-b5bc-5a516e76343a","pdf_url":null,"source":{"id":"https://openalex.org/S4306400705","display_name":"Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I96673099","host_organization_name":"Technical University of Denmark","host_organization_lineage":["https://openalex.org/I96673099"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Thrane , J , Artuso , M , Zibar , D &amp; Christiansen , H L 2018 , Drive Test Minimization Using Deep Learning with Bayesian Approximation . in Proceedings of 2018 IEEE 88th Vehicular Technology Conference . IEEE , pp. 1-5 , 2018 IEEE 88th Vehicular Technology Conference , Chicago , Illinois , United States , 27/08/2018 . https://doi.org/10.1109/VTCFall.2018.8690911","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W1497242370","https://openalex.org/W1663973292","https://openalex.org/W2088924407","https://openalex.org/W2096032932","https://openalex.org/W2160691714","https://openalex.org/W2257062227","https://openalex.org/W2575113712","https://openalex.org/W2734408173","https://openalex.org/W2769528699","https://openalex.org/W2919115771","https://openalex.org/W2964059111","https://openalex.org/W4212863985","https://openalex.org/W4239343612"],"related_works":["https://openalex.org/W2172272784","https://openalex.org/W2003817535","https://openalex.org/W4307436769","https://openalex.org/W4323793210","https://openalex.org/W2366306259","https://openalex.org/W3101720559","https://openalex.org/W2143447014","https://openalex.org/W2218045119","https://openalex.org/W3172283447","https://openalex.org/W4401858220"],"abstract_inverted_index":{"Drive":[0],"testing":[1],"is":[2],"a":[3],"common":[4],"practice":[5],"performed":[6],"by":[7,92],"operators":[8],"to":[9,18,32,52,94],"optimize":[10],"and":[11,20],"evaluate":[12],"their":[13],"mobile":[14],"networks":[15],"with":[16],"respect":[17],"capacity":[19],"coverage.":[21],"For":[22],"dense":[23],"areas,":[24],"drive":[25,59,89],"test":[26,60],"measurements":[27,75],"are":[28,76],"very":[29],"time-consuming":[30],"due":[31],"many":[33],"obstacles":[34],"causing":[35],"Non-Line-Of-Sight":[36],"(NLoS)":[37],"scenarios.":[38],"In":[39],"this":[40],"paper,":[41],"we":[42,63],"show":[43,64],"how":[44,65],"Deep":[45],"Learning":[46],"(DL)":[47],"techniques":[48],"can":[49,69,81],"be":[50],"utilized":[51],"predict":[53,83],"LTE":[54,84],"signal":[55,85],"quality":[56,86],"metrics":[57,87],"using":[58],"measurements.":[61],"Moreover,":[62],"the":[66],"obtained":[67],"solution":[68,80],"offer":[70],"insight":[71],"into":[72],"where":[73],"additional":[74],"required.":[77],"The":[78],"proposed":[79],"accurately":[82],"reducing":[88],"tests":[90],"needed":[91],"up":[93],"70%.":[95]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
