{"id":"https://openalex.org/W3172442072","doi":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448812","title":"Propagation-aware Gaussian Process Regression for Signal-Strength Interpolation along Street Canyons","display_name":"Propagation-aware Gaussian Process Regression for Signal-Strength Interpolation along Street Canyons","publication_year":2021,"publication_date":"2021-04-01","ids":{"openalex":"https://openalex.org/W3172442072","doi":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448812","mag":"3172442072"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2021-spring51267.2021.9448812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448812","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":"conference-paper","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/A5062963141","display_name":"Lukas Eller","orcid":"https://orcid.org/0000-0002-1087-0953"},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]},{"id":"https://openalex.org/I4210122474","display_name":"Forschungszentrum Telekommunikation Wien","ror":"https://ror.org/026nftk33","country_code":"AT","type":"facility","lineage":["https://openalex.org/I4210122474"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Lukas Eller","raw_affiliation_strings":["TU-Wien,Institute of Telecommunications,Vienna,Austria","Institute of Telecommunications, TU-Wien, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU-Wien,Institute of Telecommunications,Vienna,Austria","institution_ids":["https://openalex.org/I4210122474"]},{"raw_affiliation_string":"Institute of Telecommunications, TU-Wien, Vienna, Austria","institution_ids":["https://openalex.org/I145847075"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062907826","display_name":"Philipp Svoboda","orcid":"https://orcid.org/0000-0002-2277-0378"},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]},{"id":"https://openalex.org/I4210122474","display_name":"Forschungszentrum Telekommunikation Wien","ror":"https://ror.org/026nftk33","country_code":"AT","type":"facility","lineage":["https://openalex.org/I4210122474"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Philipp Svoboda","raw_affiliation_strings":["TU-Wien,Institute of Telecommunications,Vienna,Austria","Institute of Telecommunications, TU-Wien, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU-Wien,Institute of Telecommunications,Vienna,Austria","institution_ids":["https://openalex.org/I4210122474"]},{"raw_affiliation_string":"Institute of Telecommunications, TU-Wien, Vienna, Austria","institution_ids":["https://openalex.org/I145847075"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009083554","display_name":"Markus Rupp","orcid":"https://orcid.org/0000-0001-9003-7779"},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]},{"id":"https://openalex.org/I4210122474","display_name":"Forschungszentrum Telekommunikation Wien","ror":"https://ror.org/026nftk33","country_code":"AT","type":"facility","lineage":["https://openalex.org/I4210122474"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Markus Rupp","raw_affiliation_strings":["TU-Wien,Institute of Telecommunications,Vienna,Austria","Institute of Telecommunications, TU-Wien, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU-Wien,Institute of Telecommunications,Vienna,Austria","institution_ids":["https://openalex.org/I4210122474"]},{"raw_affiliation_string":"Institute of Telecommunications, TU-Wien, Vienna, Austria","institution_ids":["https://openalex.org/I145847075"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9944999814033508,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9944999814033508,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9930999875068665,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9868000149726868,"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":0.6755900979042053},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.588879406452179},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.57463139295578},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5675137042999268},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.45686691999435425},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.39052078127861023},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3883930444717407},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3458127975463867},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.32554903626441956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29859504103660583},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2776498794555664},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14505505561828613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6755900979042053},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.588879406452179},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.57463139295578},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5675137042999268},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.45686691999435425},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.39052078127861023},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3883930444717407},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3458127975463867},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32554903626441956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29859504103660583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2776498794555664},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14505505561828613},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2021-spring51267.2021.9448812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448812","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8399999737739563}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W14071851","https://openalex.org/W1556372134","https://openalex.org/W1663973292","https://openalex.org/W1746819321","https://openalex.org/W1991056455","https://openalex.org/W1999804650","https://openalex.org/W2009086942","https://openalex.org/W2101234009","https://openalex.org/W2113207845","https://openalex.org/W2125851474","https://openalex.org/W2309460698","https://openalex.org/W2417675050","https://openalex.org/W2755360796","https://openalex.org/W2784189955","https://openalex.org/W2807864322","https://openalex.org/W2914533952","https://openalex.org/W2963049813","https://openalex.org/W2982037468","https://openalex.org/W2984866899","https://openalex.org/W2990899218","https://openalex.org/W3123855443","https://openalex.org/W4211049957","https://openalex.org/W6600552058","https://openalex.org/W6675354045","https://openalex.org/W6677088747","https://openalex.org/W6678538660"],"related_works":["https://openalex.org/W4285326088","https://openalex.org/W1993996173","https://openalex.org/W2055080101","https://openalex.org/W4286247444","https://openalex.org/W3200148366","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W2056958800"],"abstract_inverted_index":{"Providing":[0],"accurate":[1],"estimates":[2],"for":[3,82],"Key":[4],"Performance":[5],"Indicators":[6],"(KPIs)":[7],"of":[8,35,53,154,191],"mobile":[9],"cellular":[10],"networks":[11],"is":[12,62,125,162],"crucial":[13],"to":[14,44,128,165,174,188],"fulfill":[15],"agreed-upon":[16],"service":[17],"requirements.":[18],"Typically,":[19],"such":[20],"performance":[21],"maps":[22],"are":[23,28,78],"based":[24,95],"on":[25,96,111],"measurements,":[26],"which":[27,101],"expensive":[29],"and":[30,70,135,177],"only":[31],"offer":[32],"sparse":[33],"samples":[34],"the":[36,47,51,59,107,138,146,158,166],"underlying":[37],"ground-truth.":[38],"Therefore,":[39,160],"we":[40,89,120],"require":[41],"interpolation":[42,85,93],"schemes":[43],"further":[45],"increase":[46],"spatial":[48],"resolution":[49],"in":[50,83,113,156,204,208,214],"area":[52],"interest.":[54],"In":[55],"dense":[56],"urban":[57],"areas,":[58],"propagation":[60],"environment":[61],"often":[63],"governed":[64],"by":[65,73,132,184],"tunneling":[66,133],"effects":[67,134],"along":[68],"streets":[69],"blockages":[71,176],"introduced":[72],"buildings.":[74],"However,":[75],"these":[76],"aspects":[77],"typically":[79],"not":[80,163],"accounted":[81],"state-of-the-art":[84],"approaches.":[86],"As":[87],"such,":[88],"propose":[90],"a":[91,114,151,189,205],"propagation-aware":[92],"scheme":[94,149],"Gaussian":[97],"Process":[98],"Regression":[99],"(GPR),":[100],"utilizes":[102],"available":[103],"geospatial":[104],"information":[105],"via":[106],"diffusion":[108],"kernel.":[109,144],"Based":[110],"simulations":[112],"stochastic":[115],"Manhattan":[116],"Grid":[117],"(MG)":[118],"environment,":[119],"show":[121,182],"that":[122],"our":[123,186],"approach":[124,187],"well":[126],"equipped":[127],"handle":[129],"environments":[130],"dominated":[131],"significantly":[136],"outperforms":[137],"omnidirectional":[139],"Radial":[140],"Basis":[141],"Function":[142],"(RBF)":[143],"Further,":[145],"proposed":[147],"graph-based":[148],"offers":[150],"high":[152],"degree":[153],"flexibility":[155],"modeling":[157],"environment.":[159],"it":[161],"specific":[164],"MG":[167],"scenario":[168],"but":[169],"can":[170],"easily":[171],"be":[172],"extended":[173],"generic":[175],"real-world":[178],"street":[179],"layouts.":[180],"We":[181],"this":[183],"applying":[185],"set":[190],"Reference":[192],"Signal":[193],"Received":[194],"Power":[195],"(RSRP)":[196],"measurements":[197],"from":[198],"an":[199,215],"operational":[200],"LTE":[201],"network":[202],"collected":[203],"drive-test":[206],"campaign":[207],"Vienna,":[209],"Austria":[210],"\u2014":[211],"again":[212],"resulting":[213],"error":[216],"reduction.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}