{"id":"https://openalex.org/W4400232345","doi":"https://doi.org/10.1109/vnc61989.2024.10575996","title":"Deep Learning Based Handover for High-Speed Connected Vehicles in Ultra-Dense Networks","display_name":"Deep Learning Based Handover for High-Speed Connected Vehicles in Ultra-Dense Networks","publication_year":2024,"publication_date":"2024-05-29","ids":{"openalex":"https://openalex.org/W4400232345","doi":"https://doi.org/10.1109/vnc61989.2024.10575996"},"language":"en","primary_location":{"id":"doi:10.1109/vnc61989.2024.10575996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vnc61989.2024.10575996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Vehicular Networking Conference (VNC)","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/A5100410680","display_name":"Zhi Zhang","orcid":"https://orcid.org/0000-0001-8672-6766"},"institutions":[{"id":"https://openalex.org/I47605537","display_name":"Hang Seng University of Hong Kong","ror":"https://ror.org/04fa64g55","country_code":"HK","type":"education","lineage":["https://openalex.org/I47605537"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhi Zhang","raw_affiliation_strings":["The Hang Seng University of Hong Kong,Department of Computer Science,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hang Seng University of Hong Kong,Department of Computer Science,Hong Kong SAR,China","institution_ids":["https://openalex.org/I47605537","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050923123","display_name":"Yun Hou","orcid":"https://orcid.org/0000-0002-5206-4554"},"institutions":[{"id":"https://openalex.org/I47605537","display_name":"Hang Seng University of Hong Kong","ror":"https://ror.org/04fa64g55","country_code":"HK","type":"education","lineage":["https://openalex.org/I47605537"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yun Hou","raw_affiliation_strings":["The Hang Seng University of Hong Kong,Department of Computer Science,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hang Seng University of Hong Kong,Department of Computer Science,Hong Kong SAR,China","institution_ids":["https://openalex.org/I47605537","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101390807","display_name":"Pang-Sik Hui","orcid":null},"institutions":[{"id":"https://openalex.org/I4210086892","display_name":"Education University of Hong Kong","ror":"https://ror.org/000t0f062","country_code":"HK","type":"education","lineage":["https://openalex.org/I4210086892"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Pang-Sik Hui","raw_affiliation_strings":["The Education University of Hong Kong,Department of Mathematics and Information Technology,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Education University of Hong Kong,Department of Mathematics and Information Technology,Hong Kong SAR,China","institution_ids":["https://openalex.org/I4210086892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102917922","display_name":"Chunhua Sun","orcid":"https://orcid.org/0000-0003-0385-6747"},"institutions":[{"id":"https://openalex.org/I4210127700","display_name":"Zhejiang Shuren University","ror":"https://ror.org/0331z5r71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210127700"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhua Sun","raw_affiliation_strings":["College of Information Science and Technology, Zhejiang Shuren University,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Zhejiang Shuren University,China","institution_ids":["https://openalex.org/I4210127700"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"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":"290","last_page":"296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11504","display_name":"Advanced Authentication Protocols Security","score":0.9398000240325928,"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"}},"topics":[{"id":"https://openalex.org/T11504","display_name":"Advanced Authentication Protocols Security","score":0.9398000240325928,"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/T11932","display_name":"Wireless Body Area Networks","score":0.90829998254776,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9035000205039978,"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/handover","display_name":"Handover","score":0.7696834802627563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6783521175384521},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44484761357307434},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4215776324272156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3718189001083374}],"concepts":[{"id":"https://openalex.org/C111852164","wikidata":"https://www.wikidata.org/wiki/Q1414679","display_name":"Handover","level":2,"score":0.7696834802627563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6783521175384521},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44484761357307434},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4215776324272156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3718189001083374}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vnc61989.2024.10575996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vnc61989.2024.10575996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Vehicular Networking Conference (VNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2520149731","https://openalex.org/W2903920444","https://openalex.org/W2970518786","https://openalex.org/W3045610054","https://openalex.org/W3100777112","https://openalex.org/W3185800695","https://openalex.org/W3203070414","https://openalex.org/W4210761538"],"related_works":["https://openalex.org/W2270230623","https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756"],"abstract_inverted_index":{"In":[0,79],"Vehicle-to-Everything":[1],"(V2X)":[2],"applications,":[3],"vehi-cles":[4],"pass":[5],"through":[6],"network":[7,176,199],"cells":[8,128],"at":[9],"high":[10,48],"speeds,":[11],"with":[12,61,95,165],"ultra-":[13],"dense":[14],"deployments":[15],"of":[16,138,180,188,205],"base":[17,59],"stations,":[18],"frequent":[19,77],"handover":[20,54,86,103,117,153,201],"becomes":[21],"a":[22,36,84],"prominent":[23],"issue":[24],"to":[25,40,74,90,116,162],"be":[26,163],"addressed.":[27],"Especially":[28],"in":[29,208],"V2X":[30],"road-":[31],"safety":[32],"use":[33],"cases,":[34],"maintaining":[35],"long-term":[37],"stable":[38],"connection":[39],"the":[41,52,58,62,68,92,104,110,114,125,133,166,196],"cell":[42,94,112],"is":[43,129],"more":[44,76],"important":[45],"than":[46],"having":[47],"immediate":[49],"throughput.":[50],"Therefore,":[51],"traditional":[53],"scheme":[55,87,154],"that":[56,88,101,171,195],"selects":[57],"station":[60],"highest":[63],"signal":[64,140],"strength":[65],"without":[66,113],"considering":[67],"remaining":[69,97,121,181],"dwell":[70,98,122,182],"time":[71,123,183],"may":[72],"lead":[73],"even":[75],"handovers.":[78],"this":[80],"paper,":[81],"we":[82],"propose":[83],"new":[85,111,152],"aims":[89],"select":[91],"target":[93,127],"maximal":[96],"time,":[99],"such":[100],"after":[102],"user":[105,134,160],"equipment":[106],"will":[107],"camp":[108],"on":[109,132],"need":[115],"again":[118],"soon.":[119],"The":[120,151],"for":[124],"potential":[126],"predicted":[130],"based":[131,200],"equipment's":[135],"local":[136],"measurement":[137],"received":[139],"strength,":[141],"driving":[142],"speed":[143],"and":[144],"direction":[145],"using":[146],"ID-CNN":[147],"deep":[148,174,197],"learning":[149,175,198],"networks.":[150],"does":[155],"not":[156],"require":[157],"any":[158],"private":[159],"information":[161],"exchanged":[164],"BS.":[167],"Validation":[168],"results":[169,193],"show":[170],"our":[172],"ID-CNN-based":[173],"provides":[177],"high-accuracy":[178],"predictions":[179],"achieving":[184],"an":[185],"R2":[186],"score":[187],"0.96.":[189],"Network":[190],"level":[191],"simulation":[192],"demonstrate":[194],"can":[202],"reduce":[203],"74%":[204],"unnecessary":[206],"handovers":[207],"ultra-dense":[209],"scenarios.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}