{"id":"https://openalex.org/W3170403201","doi":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448806","title":"Terminal-Side Data Rate Prediction For High-Mobility Users","display_name":"Terminal-Side Data Rate Prediction For High-Mobility Users","publication_year":2021,"publication_date":"2021-04-01","ids":{"openalex":"https://openalex.org/W3170403201","doi":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448806","mag":"3170403201"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2021-spring51267.2021.9448806","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448806","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","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/A5068710820","display_name":"Daniel Sch\u00e4ufele","orcid":"https://orcid.org/0000-0002-7334-9321"},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Daniel Schaufele","raw_affiliation_strings":["Fraunhofer Heinrich Hertz Institute,Wireless Communications and Networks,Berlin,Germany","Wireless Communications and Networks, Fraunhofer Heinrich Hertz Institute, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Heinrich Hertz Institute,Wireless Communications and Networks,Berlin,Germany","institution_ids":["https://openalex.org/I2800274787"]},{"raw_affiliation_string":"Wireless Communications and Networks, Fraunhofer Heinrich Hertz Institute, Berlin, Germany","institution_ids":["https://openalex.org/I2800274787"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048657850","display_name":"Martin Kasparick","orcid":"https://orcid.org/0000-0002-9214-6976"},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Kasparick","raw_affiliation_strings":["Fraunhofer Heinrich Hertz Institute,Wireless Communications and Networks,Berlin,Germany","Wireless Communications and Networks, Fraunhofer Heinrich Hertz Institute, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Heinrich Hertz Institute,Wireless Communications and Networks,Berlin,Germany","institution_ids":["https://openalex.org/I2800274787"]},{"raw_affiliation_string":"Wireless Communications and Networks, Fraunhofer Heinrich Hertz Institute, Berlin, Germany","institution_ids":["https://openalex.org/I2800274787"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057078746","display_name":"Jens Schwardmann","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128710","display_name":"Robert Bosch (United Kingdom)","ror":"https://ror.org/031zzq071","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210128710","https://openalex.org/I889804353"]},{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE","GB"],"is_corresponding":false,"raw_author_name":"Jens Schwardmann","raw_affiliation_strings":["Corporate Research,Robert Bosch GmbH,Hildesheim,Germany","Robert Bosch GmbH, Corporate Research, Hildesheim, Germany"],"affiliations":[{"raw_affiliation_string":"Corporate Research,Robert Bosch GmbH,Hildesheim,Germany","institution_ids":["https://openalex.org/I889804353","https://openalex.org/I4210128710"]},{"raw_affiliation_string":"Robert Bosch GmbH, Corporate Research, Hildesheim, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029009905","display_name":"Johannes Morgenroth","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]},{"id":"https://openalex.org/I4210128710","display_name":"Robert Bosch (United Kingdom)","ror":"https://ror.org/031zzq071","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210128710","https://openalex.org/I889804353"]}],"countries":["DE","GB"],"is_corresponding":false,"raw_author_name":"Johannes Morgenroth","raw_affiliation_strings":["Corporate Research,Robert Bosch GmbH,Hildesheim,Germany","Robert Bosch GmbH, Corporate Research, Hildesheim, Germany"],"affiliations":[{"raw_affiliation_string":"Corporate Research,Robert Bosch GmbH,Hildesheim,Germany","institution_ids":["https://openalex.org/I889804353","https://openalex.org/I4210128710"]},{"raw_affiliation_string":"Robert Bosch GmbH, Corporate Research, Hildesheim, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068274314","display_name":"S\u0142awomir Sta\u0144czak","orcid":"https://orcid.org/0000-0003-3829-4668"},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Slawomir Stanczak","raw_affiliation_strings":["Fraunhofer Heinrich Hertz Institute,Wireless Communications and Networks,Berlin,Germany","Wireless Communications and Networks, Fraunhofer Heinrich Hertz Institute, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Heinrich Hertz Institute,Wireless Communications and Networks,Berlin,Germany","institution_ids":["https://openalex.org/I2800274787"]},{"raw_affiliation_string":"Wireless Communications and Networks, Fraunhofer Heinrich Hertz Institute, Berlin, Germany","institution_ids":["https://openalex.org/I2800274787"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5068710820"],"corresponding_institution_ids":["https://openalex.org/I2800274787"],"apc_list":null,"apc_paid":null,"fwci":1.3593,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.8299777,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T13553","display_name":"Age of Information Optimization","score":0.9957000017166138,"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"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/telecommunications-link","display_name":"Telecommunications link","score":0.8366208076477051},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7724020481109619},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6532178521156311},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6021422147750854},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5486413836479187},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49460312724113464},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48800888657569885},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.4870467483997345},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.46477821469306946},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.44494086503982544},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44152015447616577},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4206688702106476},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.37892696261405945},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.21554097533226013},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08466103672981262}],"concepts":[{"id":"https://openalex.org/C138660444","wikidata":"https://www.wikidata.org/wiki/Q5607897","display_name":"Telecommunications link","level":2,"score":0.8366208076477051},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7724020481109619},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6532178521156311},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6021422147750854},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5486413836479187},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49460312724113464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48800888657569885},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.4870467483997345},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.46477821469306946},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.44494086503982544},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44152015447616577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4206688702106476},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.37892696261405945},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.21554097533226013},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08466103672981262},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/vtc2021-spring51267.2021.9448806","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448806","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-641267","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-641267.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer HHI","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/413125","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/413125","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1573647811","https://openalex.org/W2167250202","https://openalex.org/W2295598076","https://openalex.org/W2784189955","https://openalex.org/W2785781794","https://openalex.org/W2899494475","https://openalex.org/W2910166370","https://openalex.org/W2911964244","https://openalex.org/W2942480541","https://openalex.org/W2965762776","https://openalex.org/W2971169014","https://openalex.org/W3011023724","https://openalex.org/W3102476541","https://openalex.org/W4288358532","https://openalex.org/W6634147026","https://openalex.org/W6684388392","https://openalex.org/W6762839895"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W2885516856","https://openalex.org/W4289703016","https://openalex.org/W3094138326","https://openalex.org/W4310224730"],"abstract_inverted_index":{"The":[0],"possibility":[1],"of":[2,5,37,81,143],"predicting":[3,148],"Quality":[4],"Service,":[6],"and":[7,21,35,53,65,98,105,122,165],"particularly":[8,132],"data":[9,30,51,67,92,153],"rates,":[10],"in":[11,70,96,117,120],"mobile":[12],"networks":[13,164],"will":[14],"enable":[15],"new":[16],"applications":[17],"for":[18,78,100,134,147],"future":[19],"automated":[20],"connected":[22],"mobility,":[23],"such":[24],"as":[25],"teleoperated":[26],"driving.":[27],"Since":[28],"network":[29],"is":[31,131],"difficult":[32],"to":[33,47],"acquire":[34],"usually":[36],"low":[38],"granularity,":[39],"robust":[40],"prediction":[41,94,136],"approaches":[42],"are":[43,75],"required":[44],"that":[45,74,157],"need":[46],"be":[48],"trained":[49],"with":[50,125,171],"sets":[52],"measurements":[54],"generated":[55],"by":[56],"end":[57],"devices.":[58],"In":[59],"this":[60,87],"paper,":[61],"we":[62,89,139],"present":[63],"uplink":[64,97,118],"downlink":[66,99],"sets,":[68,128],"measured":[69],"extensive":[71],"drive":[72],"tests,":[73],"made":[76],"available":[77],"the":[79,91,135,141,151],"evaluation":[80],"machine":[82],"learning":[83],"methods.":[84],"Based":[85],"on":[86,150,162],"data,":[88],"compare":[90],"rate":[93],"performance":[95],"neural":[101,163],"network,":[102],"random":[103,166],"forest":[104],"gradient":[106,129],"boosting":[107,130],"approaches.":[108],"Our":[109],"results":[110],"show":[111,156],"a":[112],"significantly":[113],"higher":[114],"achievable":[115,152],"accuracy":[116],"than":[119],"downlink,":[121],"that,":[123],"even":[124],"reduced":[126],"feature":[127],"suited":[133],"task.":[137],"Moreover,":[138],"investigate":[140],"use":[142],"quantile":[144],"estimation":[145],"methods":[146],"bounds":[149],"rate.":[154],"We":[155],"conformalized":[158],"approaches,":[159],"both":[160],"based":[161],"forests,":[167],"can":[168],"predict":[169],"quantiles":[170],"very":[172],"high":[173],"accuracy.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}