{"id":"https://openalex.org/W3033789406","doi":"https://doi.org/10.1109/tvt.2020.2999313","title":"Multi-Feature Fusion Based Recognition and Relevance Analysis of Propagation Scenes for High-Speed Railway Channels","display_name":"Multi-Feature Fusion Based Recognition and Relevance Analysis of Propagation Scenes for High-Speed Railway Channels","publication_year":2020,"publication_date":"2020-06-02","ids":{"openalex":"https://openalex.org/W3033789406","doi":"https://doi.org/10.1109/tvt.2020.2999313","mag":"3033789406"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2020.2999313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.2999313","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","raw_type":"journal-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/A5087504521","display_name":"Tao Zhou","orcid":"https://orcid.org/0000-0001-9908-255X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]},{"id":"https://openalex.org/I4210141966","display_name":"China Academy of Railway Sciences","ror":"https://ror.org/051wv2j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141966"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Zhou","raw_affiliation_strings":["Center of National Railway Intelligent Transportation System Engineering and Technology, China Academy of Railway Sciences, Beijing, China","Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9908-255X","affiliations":[{"raw_affiliation_string":"Center of National Railway Intelligent Transportation System Engineering and Technology, China Academy of Railway Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210141966"]},{"raw_affiliation_string":"Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349995","display_name":"Yingjie Wang","orcid":"https://orcid.org/0000-0001-8792-8570"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Wang","raw_affiliation_strings":["Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8792-8570","affiliations":[{"raw_affiliation_string":"Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100779393","display_name":"Cheng\u2010Xiang Wang","orcid":"https://orcid.org/0000-0002-9729-9592"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng-Xiang Wang","raw_affiliation_strings":["National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","Purple Mountain Laboratories, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9729-9592","affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011458272","display_name":"Sana Salous","orcid":"https://orcid.org/0000-0002-4227-9893"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sana Salous","raw_affiliation_strings":["School of Engineering and Computing Sciences, Durham University, Durham, U.K"],"raw_orcid":"https://orcid.org/0000-0002-4227-9893","affiliations":[{"raw_affiliation_string":"School of Engineering and Computing Sciences, Durham University, Durham, U.K","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002989451","display_name":"Liu Liu","orcid":"https://orcid.org/0000-0002-7142-7621"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liu Liu","raw_affiliation_strings":["Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7142-7621","affiliations":[{"raw_affiliation_string":"Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100712797","display_name":"Cheng Tao","orcid":"https://orcid.org/0000-0001-9670-8545"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Tao","raw_affiliation_strings":["Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5087504521"],"corresponding_institution_ids":["https://openalex.org/I21193070","https://openalex.org/I4210141966"],"apc_list":null,"apc_paid":null,"fwci":2.4968,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.89646359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"69","issue":"8","first_page":"8107","last_page":"8118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9958000183105469,"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":0.9958000183105469,"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/T13905","display_name":"Telecommunications and Broadcasting Technologies","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.9700999855995178,"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/support-vector-machine","display_name":"Support vector machine","score":0.6396012902259827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6101676821708679},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5808573365211487},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5605390667915344},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5321896076202393},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4938293397426605},{"id":"https://openalex.org/keywords/confusion-matrix","display_name":"Confusion matrix","score":0.47024860978126526},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4700274169445038},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42890042066574097},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36878523230552673},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15344223380088806}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6396012902259827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6101676821708679},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5808573365211487},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5605390667915344},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5321896076202393},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4938293397426605},{"id":"https://openalex.org/C138602881","wikidata":"https://www.wikidata.org/wiki/Q2709591","display_name":"Confusion matrix","level":2,"score":0.47024860978126526},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4700274169445038},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42890042066574097},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36878523230552673},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15344223380088806},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2020.2999313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.2999313","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G2475888850","display_name":null,"funder_award_id":"2020B01","funder_id":"https://openalex.org/F4320324856","funder_display_name":"Southeast University"},{"id":"https://openalex.org/G2734937587","display_name":null,"funder_award_id":"61960206006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4133240970","display_name":null,"funder_award_id":"61701017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5933431147","display_name":null,"funder_award_id":"2242020R30001","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324856","display_name":"Southeast University","ror":"https://ror.org/04ct4d772"},{"id":"https://openalex.org/F4320328872","display_name":"China Academy of Railway Sciences","ror":"https://ror.org/051wv2j09"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1653024839","https://openalex.org/W1677182931","https://openalex.org/W1922250139","https://openalex.org/W1981920455","https://openalex.org/W2000982899","https://openalex.org/W2014774844","https://openalex.org/W2016053056","https://openalex.org/W2037986567","https://openalex.org/W2041528569","https://openalex.org/W2073147814","https://openalex.org/W2085190994","https://openalex.org/W2096032932","https://openalex.org/W2102113734","https://openalex.org/W2113242816","https://openalex.org/W2116753260","https://openalex.org/W2119821739","https://openalex.org/W2120201680","https://openalex.org/W2131048655","https://openalex.org/W2156303437","https://openalex.org/W2163001348","https://openalex.org/W2163605009","https://openalex.org/W2192171512","https://openalex.org/W2308045930","https://openalex.org/W2333715204","https://openalex.org/W2343196563","https://openalex.org/W2406520110","https://openalex.org/W2508720818","https://openalex.org/W2526479943","https://openalex.org/W2549114029","https://openalex.org/W2568408353","https://openalex.org/W2595146733","https://openalex.org/W2600156789","https://openalex.org/W2602960042","https://openalex.org/W2618530766","https://openalex.org/W2739748921","https://openalex.org/W2745902057","https://openalex.org/W2748760676","https://openalex.org/W2775421175","https://openalex.org/W2777547807","https://openalex.org/W2792345332","https://openalex.org/W2807731816","https://openalex.org/W2888108833","https://openalex.org/W2890445686","https://openalex.org/W2895671305","https://openalex.org/W2896144685","https://openalex.org/W2900841156","https://openalex.org/W2900911136","https://openalex.org/W2903749698","https://openalex.org/W2921604001","https://openalex.org/W2941060115","https://openalex.org/W2948169568","https://openalex.org/W2953741952","https://openalex.org/W2964121744","https://openalex.org/W2965646537","https://openalex.org/W3018241135","https://openalex.org/W4239510810","https://openalex.org/W6631190155","https://openalex.org/W6660976402","https://openalex.org/W6675365184","https://openalex.org/W6682864246","https://openalex.org/W6727499575","https://openalex.org/W6741832134","https://openalex.org/W7071026915"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W4396689146","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W2004826645","https://openalex.org/W4205685985","https://openalex.org/W2551890981","https://openalex.org/W4288025700","https://openalex.org/W1980222719"],"abstract_inverted_index":{"This":[0,111],"paper":[1],"proposes":[2],"a":[3,88],"multi-feature":[4],"fusion":[5,91,114],"based":[6,115],"propagation":[7],"scene":[8],"recognition":[9],"model":[10,74,86,117],"for":[11,72,107],"high-speed":[12],"railway":[13,46],"(HSR)":[14],"channels":[15],"and":[16,37,67,76,120,129,154,173,183,206],"presents":[17],"the":[18,43,73,81,94,104,159,190,198,204],"channel":[19,55,160,201],"relevance":[20,82,161,202],"analysis":[21],"of":[22,45,53,124,162,169,176],"HSR":[23,31,163],"scenes.":[24,208],"Extensive":[25],"field":[26],"measurement":[27],"data":[28],"in":[29,99,122,189],"typical":[30],"scenes,":[32,39],"including":[33],"rural,":[34],"station,":[35],"suburban":[36,207],"multi-link":[38,205],"are":[40,70,187,194],"collected":[41],"with":[42],"assist":[44],"long-term":[47],"evolution":[48],"(LTE)":[49],"networks.":[50],"The":[51,84],"datasets":[52],"space-time-frequency":[54],"features,":[56],"involving":[57],"Ricean":[58],"K-factor,":[59],"root":[60],"mean":[61],"square":[62],"delay":[63],"spread,":[64,66,69],"Doppler":[65],"angle":[68],"generated":[71],"training":[75],"testing":[77],"as":[78,80],"well":[79],"analysis.":[83,191],"proposed":[85],"merges":[87],"weighted":[89,112,155],"score":[90,113],"scheme":[92],"into":[93],"deep":[95],"neural":[96],"network":[97],"(DNN)":[98],"order":[100],"to":[101],"adaptively":[102],"determine":[103],"optimal":[105],"weights":[106],"each":[108],"feature":[109],"stream.":[110],"DNN":[116],"is":[118,165],"implemented":[119],"evaluated":[121],"terms":[123],"accuracy,":[125],"confusion":[126],"matrix,":[127],"F-score,":[128],"receiver":[130],"operating":[131],"characteristic":[132],"(ROC)":[133],"curve,":[134],"which":[135,196],"exhibits":[136],"better":[137],"performance":[138],"than":[139],"other":[140],"machine":[141,149],"learning":[142],"models":[143],"like":[144],"random":[145],"forest,":[146],"support":[147],"vector":[148],"(SVM),":[150],"k-nearest":[151],"neighbor":[152],"(KNN),":[153],"KNN.":[156],"In":[157],"addition,":[158],"scenes":[164],"analyzed":[166],"from":[167],"perspectives":[168],"high-dimensional":[170],"distribution":[171],"distance":[172,182],"joint":[174],"correlation":[175,184],"multiple":[177],"features.":[178],"Two":[179],"metrics,":[180],"Wasserstein":[181],"matrix":[185],"collinearity,":[186],"used":[188],"Statistical":[192],"results":[193],"provided,":[195],"reveals":[197],"relatively":[199],"strong":[200],"between":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}