{"id":"https://openalex.org/W3133465808","doi":"https://doi.org/10.1109/vtc2020-fall49728.2020.9348557","title":"Transfer Learning-Based Received Power Prediction with Ray-tracing Simulation and Small Amount of Measurement Data","display_name":"Transfer Learning-Based Received Power Prediction with Ray-tracing Simulation and Small Amount of Measurement Data","publication_year":2020,"publication_date":"2020-11-01","ids":{"openalex":"https://openalex.org/W3133465808","doi":"https://doi.org/10.1109/vtc2020-fall49728.2020.9348557","mag":"3133465808"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2020-fall49728.2020.9348557","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2020-fall49728.2020.9348557","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 92nd Vehicular Technology Conference (VTC2020-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/A5110657561","display_name":"Masahiro Iwasaki","orcid":null},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masahiro Iwasaki","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042195263","display_name":"Takayuki Nishio","orcid":"https://orcid.org/0000-0003-1026-319X"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takayuki Nishio","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101694405","display_name":"Masahiro Morikura","orcid":"https://orcid.org/0000-0002-3634-1320"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Morikura","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063642951","display_name":"Koji Yamamoto","orcid":"https://orcid.org/0000-0003-4106-3983"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Yamamoto","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110657561"],"corresponding_institution_ids":["https://openalex.org/I22299242"],"apc_list":null,"apc_paid":null,"fwci":0.5137,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.66090296,"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":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9950000047683716,"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/T12146","display_name":"Power Line Communications and Noise","score":0.9939000010490417,"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":0.8120777606964111},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.640616774559021},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6098799705505371},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5576333403587341},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.5276122093200684},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4829244315624237},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4592044949531555},{"id":"https://openalex.org/keywords/ray-tracing","display_name":"Ray tracing (physics)","score":0.45277056097984314},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4517464339733124},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.4456442892551422},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.43336498737335205},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.4194570481777191}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8120777606964111},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.640616774559021},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6098799705505371},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5576333403587341},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.5276122093200684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4829244315624237},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4592044949531555},{"id":"https://openalex.org/C121483023","wikidata":"https://www.wikidata.org/wiki/Q7298343","display_name":"Ray tracing (physics)","level":2,"score":0.45277056097984314},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4517464339733124},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.4456442892551422},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.43336498737335205},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4194570481777191},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2020-fall49728.2020.9348557","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2020-fall49728.2020.9348557","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1506524755","https://openalex.org/W1836465849","https://openalex.org/W2004993104","https://openalex.org/W2054405892","https://openalex.org/W2084801029","https://openalex.org/W2099878889","https://openalex.org/W2117728182","https://openalex.org/W2117997407","https://openalex.org/W2132231561","https://openalex.org/W2147016173","https://openalex.org/W2157693833","https://openalex.org/W2161674664","https://openalex.org/W2277193968","https://openalex.org/W2574081677","https://openalex.org/W2616222121","https://openalex.org/W2954996726","https://openalex.org/W2963079272","https://openalex.org/W2963390419","https://openalex.org/W2972468666","https://openalex.org/W3140332775","https://openalex.org/W6638667902","https://openalex.org/W6767844734"],"related_works":["https://openalex.org/W618248309","https://openalex.org/W2377336366","https://openalex.org/W1568097102","https://openalex.org/W4239286941","https://openalex.org/W4390419160","https://openalex.org/W1601203902","https://openalex.org/W2088845016","https://openalex.org/W2075798043","https://openalex.org/W589102260","https://openalex.org/W3171384686"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,16,26,56,61,96,108,129],"method":[4,100,106,153],"to":[5,46,69,81,135],"predict":[6,47],"received":[7,155],"power":[8,156],"in":[9,35,71],"urban":[10],"area":[11],"deterministically,":[12],"which":[13,66],"can":[14],"learn":[15],"prediction":[17,84,99,109],"model":[18,59,110,130],"from":[19,114],"small":[20,86],"amount":[21,87],"of":[22,64,88,120,161,165],"measurement":[23,89],"data":[24,31,102,112,121,124,134],"by":[25],"simulation-aided":[27],"transfer":[28,97],"learning":[29,37],"and":[30,50,126,146],"augmentation.":[32,103],"Recent":[33],"development":[34],"machine":[36],"such":[38],"as":[39],"artificial":[40],"neural":[41],"network":[42],"(ANN)":[43],"enables":[44],"us":[45],"radio":[48],"propagation":[49],"path":[51],"loss":[52],"accurately.":[53],"However,":[54],"training":[55],"high-performance":[57],"ANN":[58],"requires":[60],"significant":[62],"number":[63,119],"data,":[65],"are":[67],"difficult":[68],"obtain":[70],"real":[72],"environments.":[73],"The":[74,104],"main":[75],"motivation":[76],"for":[77],"this":[78,92],"work":[79],"was":[80],"facilitate":[82],"accurate":[83],"using":[85,111,122,131,141],"data.":[90],"To":[91],"end,":[93],"we":[94],"propose":[95],"learning-based":[98],"with":[101,157],"proposed":[105,152],"pre-trains":[107],"generated":[113],"ray-tracing":[115],"simulations,":[116],"increases":[117],"the":[118,132,137,147,151,162],"simulation-assisted":[123],"augmentation,":[125],"then":[127],"fine-tunes":[128],"augmented":[133],"fit":[136],"target":[138],"environment.":[139],"Experiments":[140],"Wi-Fi":[142],"devices":[143],"were":[144],"conducted,":[145],"results":[148],"demonstrate":[149],"that":[150],"predicts":[154],"50%":[158],"(or":[159],"less)":[160],"RMS":[163],"error":[164],"conventional":[166],"methods.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-02-25T23:00:34.991745","created_date":"2025-10-10T00:00:00"}
