{"id":"https://openalex.org/W4403759146","doi":"https://doi.org/10.1109/lcomm.2024.3486166","title":"Rescale-Invariant Federated Reinforcement Learning for Resource Allocation in V2X Networks","display_name":"Rescale-Invariant Federated Reinforcement Learning for Resource Allocation in V2X Networks","publication_year":2024,"publication_date":"2024-10-25","ids":{"openalex":"https://openalex.org/W4403759146","doi":"https://doi.org/10.1109/lcomm.2024.3486166"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2024.3486166","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2024.3486166","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","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 Communications Letters","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/A5011173717","display_name":"Kaidi Xu","orcid":"https://orcid.org/0000-0002-0719-3912"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kaidi Xu","raw_affiliation_strings":["Department of EEE, ITP Laboratory, Imperial College London, London, U.K","ITP Lab, Department of EEE, Imperial College London, UK"],"raw_orcid":"https://orcid.org/0000-0002-0719-3912","affiliations":[{"raw_affiliation_string":"Department of EEE, ITP Laboratory, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"ITP Lab, Department of EEE, Imperial College London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023017250","display_name":"Shenglong Zhou","orcid":"https://orcid.org/0000-0003-2843-1614"},"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":"Shenglong Zhou","raw_affiliation_strings":["School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, China","School of Mathematics and Statistics, Beijing Jiaotong University, China"],"raw_orcid":"https://orcid.org/0000-0003-2843-1614","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Beijing Jiaotong University, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039289964","display_name":"Geoffrey Ye Li","orcid":"https://orcid.org/0000-0002-7894-2415"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Geoffrey Ye Li","raw_affiliation_strings":["Department of EEE, ITP Laboratory, Imperial College London, London, U.K","ITP Lab, Department of EEE, Imperial College London, UK"],"raw_orcid":"https://orcid.org/0000-0002-7894-2415","affiliations":[{"raw_affiliation_string":"Department of EEE, ITP Laboratory, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"ITP Lab, Department of EEE, Imperial College London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2488,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.81622293,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"28","issue":"12","first_page":"2799","last_page":"2803"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9879000186920166,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9879000186920166,"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/T13553","display_name":"Age of Information Optimization","score":0.9751999974250793,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.9387000203132629,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8117789030075073},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7329300045967102},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.6534705758094788},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.5076838731765747},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.43421459197998047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3922445476055145},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.36379167437553406},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3364773392677307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12135067582130432}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8117789030075073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7329300045967102},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6534705758094788},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.5076838731765747},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.43421459197998047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3922445476055145},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.36379167437553406},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3364773392677307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12135067582130432},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2024.3486166","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2024.3486166","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","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 Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"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":13,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W2963000651","https://openalex.org/W2968764495","https://openalex.org/W2984045653","https://openalex.org/W3122846486","https://openalex.org/W3205598877","https://openalex.org/W3216388332","https://openalex.org/W4285184341","https://openalex.org/W4366492963","https://openalex.org/W6616617004","https://openalex.org/W6728757088","https://openalex.org/W6759238902","https://openalex.org/W6796527454"],"related_works":["https://openalex.org/W2923452570","https://openalex.org/W206598027","https://openalex.org/W2978610750","https://openalex.org/W2138260944","https://openalex.org/W2022931285","https://openalex.org/W1589966275","https://openalex.org/W2086872282","https://openalex.org/W2137789903","https://openalex.org/W2138781885","https://openalex.org/W2153007255"],"abstract_inverted_index":{"Federated":[0],"Reinforcement":[1],"Learning":[2],"(FRL)":[3],"offers":[4],"a":[5,67,73],"promising":[6],"solution":[7],"to":[8,57,71],"various":[9],"practical":[10],"challenges":[11],"in":[12],"resource":[13],"allocation":[14],"for":[15],"vehicle-to-everything":[16],"(V2X)":[17],"networks.":[18],"However,":[19],"the":[20,29,40,51,81],"data":[21,55],"discrepancy":[22,56],"among":[23],"individual":[24],"agents":[25],"can":[26],"significantly":[27],"degrade":[28],"performance":[30],"of":[31,44,53],"FRL-based":[32],"algorithms.":[33],"To":[34],"address":[35],"this":[36,63],"limitation,":[37],"we":[38,65],"exploit":[39],"node-wise":[41],"invariance":[42],"property":[43],"rectified":[45],"linear":[46],"unit-activated":[47],"neural":[48],"networks,":[49],"with":[50],"aim":[52],"reducing":[54],"improve":[58],"learning":[59],"performance.":[60,91],"Based":[61],"on":[62],"property,":[64],"introduce":[66],"backward":[68],"rescale-invariant":[69,74],"operation":[70],"develop":[72],"FRL":[75],"algorithm.":[76],"Simulation":[77],"results":[78],"demonstrate":[79],"that":[80],"proposed":[82],"algorithm":[83],"notably":[84],"enhances":[85],"both":[86],"convergence":[87],"speed":[88],"and":[89],"convergent":[90]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}