{"id":"https://openalex.org/W1493798362","doi":"https://doi.org/10.1109/vtcspring.2015.7145740","title":"Characterization of First and Second Order Statistics of Large Scale Fading Using Vehicular Sensors","display_name":"Characterization of First and Second Order Statistics of Large Scale Fading Using Vehicular Sensors","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1493798362","doi":"https://doi.org/10.1109/vtcspring.2015.7145740","mag":"1493798362"},"language":"en","primary_location":{"id":"doi:10.1109/vtcspring.2015.7145740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcspring.2015.7145740","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 81st Vehicular Technology Conference (VTC 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/A5017550367","display_name":"Haris Kremo","orcid":"https://orcid.org/0000-0002-4199-1053"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haris Kremo","raw_affiliation_strings":["Toyota InfoTechnology Center, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyota InfoTechnology Center, Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055865657","display_name":"Kohsuke Nakagawa","orcid":null},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kohsuke Nakagawa","raw_affiliation_strings":["University of Electro-Communications, Tokyo, Japan","Univ. of Electro-Commun., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electro-Communications, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]},{"raw_affiliation_string":"Univ. of Electro-Commun., Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053978714","display_name":"Onur Altintas","orcid":"https://orcid.org/0000-0001-9865-7358"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Onur Altintas","raw_affiliation_strings":["Toyota InfoTechnology Center, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyota InfoTechnology Center, Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764560","display_name":"Hideaki Tanaka","orcid":"https://orcid.org/0000-0002-1817-2850"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hideaki Tanaka","raw_affiliation_strings":["Toyota InfoTechnology Center, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyota InfoTechnology Center, Tokyo, Japan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054932044","display_name":"Takeo Fujii","orcid":"https://orcid.org/0000-0002-7886-5560"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeo Fujii","raw_affiliation_strings":["University of Electro-Communications, Tokyo, Japan","Univ. of Electro-Commun., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electro-Communications, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]},{"raw_affiliation_string":"Univ. of Electro-Commun., Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9991999864578247,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9983999729156494,"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/fading","display_name":"Fading","score":0.8427155613899231},{"id":"https://openalex.org/keywords/decorrelation","display_name":"Decorrelation","score":0.7926180362701416},{"id":"https://openalex.org/keywords/shadow-mapping","display_name":"Shadow mapping","score":0.7079657912254333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6893417239189148},{"id":"https://openalex.org/keywords/white-spaces","display_name":"White spaces","score":0.6350447535514832},{"id":"https://openalex.org/keywords/ultra-high-frequency","display_name":"Ultra high frequency","score":0.5365052223205566},{"id":"https://openalex.org/keywords/transmitter","display_name":"Transmitter","score":0.5211689472198486},{"id":"https://openalex.org/keywords/path-loss","display_name":"Path loss","score":0.48928162455558777},{"id":"https://openalex.org/keywords/relay","display_name":"Relay","score":0.4727650284767151},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42867106199264526},{"id":"https://openalex.org/keywords/log-distance-path-loss-model","display_name":"Log-distance path loss model","score":0.4216599762439728},{"id":"https://openalex.org/keywords/diversity-gain","display_name":"Diversity gain","score":0.41548168659210205},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3759559094905853},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.37304171919822693},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3680403232574463},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.347257137298584},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.33453235030174255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22452417016029358},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.19465693831443787},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1461542248725891},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13787841796875},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.11669832468032837},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09148603677749634}],"concepts":[{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.8427155613899231},{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.7926180362701416},{"id":"https://openalex.org/C116544410","wikidata":"https://www.wikidata.org/wiki/Q1478122","display_name":"Shadow mapping","level":2,"score":0.7079657912254333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6893417239189148},{"id":"https://openalex.org/C96391052","wikidata":"https://www.wikidata.org/wiki/Q256313","display_name":"White spaces","level":4,"score":0.6350447535514832},{"id":"https://openalex.org/C96122199","wikidata":"https://www.wikidata.org/wiki/Q628096","display_name":"Ultra high frequency","level":2,"score":0.5365052223205566},{"id":"https://openalex.org/C47798520","wikidata":"https://www.wikidata.org/wiki/Q190157","display_name":"Transmitter","level":3,"score":0.5211689472198486},{"id":"https://openalex.org/C194273485","wikidata":"https://www.wikidata.org/wiki/Q1478845","display_name":"Path loss","level":3,"score":0.48928162455558777},{"id":"https://openalex.org/C2778156585","wikidata":"https://www.wikidata.org/wiki/Q174053","display_name":"Relay","level":3,"score":0.4727650284767151},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42867106199264526},{"id":"https://openalex.org/C97316775","wikidata":"https://www.wikidata.org/wiki/Q3575778","display_name":"Log-distance path loss model","level":4,"score":0.4216599762439728},{"id":"https://openalex.org/C164785522","wikidata":"https://www.wikidata.org/wiki/Q5283966","display_name":"Diversity gain","level":4,"score":0.41548168659210205},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3759559094905853},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.37304171919822693},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3680403232574463},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.347257137298584},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.33453235030174255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22452417016029358},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.19465693831443787},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1461542248725891},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13787841796875},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.11669832468032837},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09148603677749634},{"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/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/vtcspring.2015.7145740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcspring.2015.7145740","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 81st Vehicular Technology Conference (VTC Spring)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1965290705","https://openalex.org/W2029425498","https://openalex.org/W2031269983","https://openalex.org/W2069804476","https://openalex.org/W2140452629","https://openalex.org/W2163053194"],"related_works":["https://openalex.org/W2098935768","https://openalex.org/W1558581849","https://openalex.org/W2291262581","https://openalex.org/W2004117546","https://openalex.org/W1981961788","https://openalex.org/W2166646022","https://openalex.org/W1540138521","https://openalex.org/W2123629755","https://openalex.org/W2462451278","https://openalex.org/W2103763222"],"abstract_inverted_index":{"We":[0],"propose":[1],"and":[2,57],"demonstrate":[3],"a":[4,38,46,66,75,84,99,114],"framework":[5],"for":[6,48,89,104,125],"statistical":[7],"modeling":[8],"of":[9,65,98,106,118,138],"propagation":[10],"using":[11],"spectrum":[12,102,119],"sensors":[13,24,120,150],"mounted":[14],"on":[15,25,37,69,74],"moving":[16],"vehicles.":[17],"To":[18],"illustrate":[19],"the":[20,42,54,62,145,149],"concept,":[21],"we":[22,44],"deploy":[23],"four":[26],"vehicles":[27],"to":[28,78,95],"collect":[29],"signal":[30,139],"strength":[31,140],"measurements":[32],"together":[33],"with":[34,121],"corresponding":[35],"locations":[36],"suburban":[39],"road.":[40],"From":[41],"data":[43],"build":[45],"model":[47,85],"large":[49],"scale":[50],"fading,":[51],"that":[52,135],"is,":[53],"path":[55],"loss":[56],"shadowing,":[58],"as":[59,61],"well":[60],"shadowing":[63],"correlation":[64],"TV":[67],"transmitter":[68],"two":[70],"UHF":[71],"channels.":[72],"Depending":[73],"specific":[76],"band":[77],"which":[79],"it":[80],"is":[81],"applied,":[82],"such":[83],"can":[86,141],"be":[87,142],"used":[88],"different":[90],"purposes":[91],"like":[92],"coverage":[93],"planning,":[94],"improve":[96],"accuracy":[97],"white":[100],"space":[101],"database,":[103],"selection":[105,117],"relay":[107],"nodes":[108],"in":[109,144],"an":[110],"ad-":[111],"hoc":[112],"or":[113],"mesh":[115],"network,":[116],"significant":[122],"diversity":[123],"gain":[124],"cooperative":[126],"sensing,":[127],"etc.":[128],"For":[129],"instance,":[130],"obtained":[131],"numerical":[132],"results":[133],"imply":[134],"sufficient":[136],"decorrelation":[137],"observed":[143],"experimental":[146],"area":[147],"if":[148],"are":[151],"separated":[152],"by":[153],"more":[154],"than":[155],"20m.":[156]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
