{"id":"https://openalex.org/W4414110734","doi":"https://doi.org/10.1109/access.2025.3608561","title":"Network Slice-Enabled Federated Learning for Collaborative Traffic Perception in Vehicular Edge Computing","display_name":"Network Slice-Enabled Federated Learning for Collaborative Traffic Perception in Vehicular Edge Computing","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414110734","doi":"https://doi.org/10.1109/access.2025.3608561"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3608561","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3608561","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3608561","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019497769","display_name":"He Xu","orcid":"https://orcid.org/0000-0003-2809-2237"},"institutions":[{"id":"https://openalex.org/I4210087615","display_name":"Beihai People's Hospital","ror":"https://ror.org/002m0p291","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210087615"]},{"id":"https://openalex.org/I4210160019","display_name":"Chongqing Municipal Health Commission","ror":"https://ror.org/04ce5fg13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210157972","https://openalex.org/I4210160019"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu He","raw_affiliation_strings":["Beihai Research Institute of City Planning, Chongqing, China","Beihai Research Institute of City Planning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihai Research Institute of City Planning, Chongqing, China","institution_ids":["https://openalex.org/I4210160019"]},{"raw_affiliation_string":"Beihai Research Institute of City Planning, China","institution_ids":["https://openalex.org/I4210087615"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Peizhi Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peizhi Sheng","raw_affiliation_strings":["College of Computer and Information Science, School of Software, Southwest University, Beibei, Chongqing, China","School of Software, College of Computer and Information Science, Southwest University, Beibei, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, School of Software, Southwest University, Beibei, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"School of Software, College of Computer and Information Science, Southwest University, Beibei, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046607903","display_name":"Bingquan Tao","orcid":"https://orcid.org/0009-0008-7925-4033"},"institutions":[{"id":"https://openalex.org/I1300757298","display_name":"Heilongjiang University of Science and Technology","ror":"https://ror.org/030xwyx96","country_code":"CN","type":"education","lineage":["https://openalex.org/I1300757298"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bohao Tao","raw_affiliation_strings":["School of Electronic and Information Engineering, Heilongjiang University of Science and Technology, Harbin, Heilongjiang, China"],"raw_orcid":"https://orcid.org/0009-0008-7925-4033","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Heilongjiang University of Science and Technology, Harbin, Heilongjiang, China","institution_ids":["https://openalex.org/I1300757298"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100362633","display_name":"Wenhao Li","orcid":"https://orcid.org/0000-0003-1420-8163"},"institutions":[{"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":"Wenhao Li","raw_affiliation_strings":["School of Transportation, Southeast University, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0003-1420-8163","affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12015008,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"159109","last_page":"159126"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.982699990272522,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.9476000070571899,"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/resource-allocation","display_name":"Resource allocation","score":0.541100025177002},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5268999934196472},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5206000208854675},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5164999961853027},{"id":"https://openalex.org/keywords/vehicular-ad-hoc-network","display_name":"Vehicular ad hoc network","score":0.5128999948501587},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.45329999923706055},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.44859999418258667},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.4361000061035156},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4178999960422516}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8633999824523926},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.554099977016449},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.541100025177002},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5206000208854675},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5164999961853027},{"id":"https://openalex.org/C192448918","wikidata":"https://www.wikidata.org/wiki/Q682677","display_name":"Vehicular ad hoc network","level":4,"score":0.5128999948501587},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.45329999923706055},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.41830000281333923},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4178999960422516},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4142000079154968},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.3874000012874603},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.36559998989105225},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C94523657","wikidata":"https://www.wikidata.org/wiki/Q4085781","display_name":"Wireless ad hoc network","level":3,"score":0.3427000045776367},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.326200008392334},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C203274722","wikidata":"https://www.wikidata.org/wiki/Q7001161","display_name":"Network performance","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26930001378059387},{"id":"https://openalex.org/C138020889","wikidata":"https://www.wikidata.org/wiki/Q2349659","display_name":"Collaborative learning","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25690001249313354},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2565999925136566},{"id":"https://openalex.org/C182448111","wikidata":"https://www.wikidata.org/wiki/Q7281197","display_name":"Radio resource management","level":4,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3608561","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3608561","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9c8a6a20cee4449390d73ed6cd0a609e","is_oa":true,"landing_page_url":"https://doaj.org/article/9c8a6a20cee4449390d73ed6cd0a609e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 159109-159126 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3608561","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3608561","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4324372666","https://openalex.org/W4225706866","https://openalex.org/W2914646191","https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W4313339048","https://openalex.org/W3111395152","https://openalex.org/W4313526662","https://openalex.org/W3023564924","https://openalex.org/W2942586735"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,40],"novel":[4],"network":[5,79,147],"slice-enabled":[6],"federated":[7,24,138],"learning":[8,25,139],"framework":[9,58],"for":[10,64],"collaborative":[11],"traffic":[12],"perception":[13,32,62],"in":[14,127,136],"vehicular":[15,36,54,146],"edge":[16],"computing":[17],"environments.":[18],"The":[19,57,130],"proposed":[20,108],"approach":[21,110],"integrates":[22],"channel-aware":[23],"with":[26,114],"intelligent":[27],"resource":[28,84,103,142],"allocation":[29,85],"to":[30,52],"enhance":[31],"performance":[33,113],"across":[34,101],"heterogeneous":[35],"networks.":[37],"We":[38],"establish":[39],"comprehensive":[41],"channel":[42,97],"model":[43],"incorporating":[44],"Doppler":[45],"effects,":[46],"multipath":[47],"fading,":[48],"and":[49,71,91,122,141,153],"temporal-spatial":[50],"variations":[51],"characterize":[53],"communication":[55],"dynamics.":[56],"employs":[59],"three":[60,102],"specialized":[61],"slices":[63],"visual":[65],"environment":[66,69],"perception,":[67,70,73],"radar":[68],"semantic":[72],"each":[74],"optimized":[75],"through":[76],"end-to-end":[77],"neural":[78],"architectures.":[80],"A":[81],"reinforcement":[82],"learning-based":[83],"mechanism":[86],"dynamically":[87],"manages":[88],"computational,":[89],"memory,":[90],"energy":[92,124],"resources":[93],"while":[94],"considering":[95],"real-time":[96],"conditions.":[98],"Extensive":[99],"simulations":[100],"environments":[104],"demonstrate":[105],"that":[106],"the":[107,133],"PPO-based":[109],"achieves":[111],"superior":[112],"94%":[115],"task":[116],"completion":[117],"rate,":[118],"32ms":[119],"communication-computation":[120],"latency,":[121],"3.35":[123],"efficiency":[125],"ratio":[126],"high-resource":[128],"scenarios.":[129],"results":[131],"validate":[132],"framework\u2019s":[134],"effectiveness":[135],"managing":[137],"convergence":[140],"optimization":[143],"under":[144],"varying":[145],"conditions,":[148],"significantly":[149],"outperforming":[150],"traditional":[151],"SAC":[152],"heuristic":[154],"PSO":[155],"approaches.":[156]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
