{"id":"https://openalex.org/W7154258561","doi":"https://doi.org/10.48550/arxiv.2604.09680","title":"Hybrid Hierarchical Federated Learning over 5G/NextG Wireless Networking","display_name":"Hybrid Hierarchical Federated Learning over 5G/NextG Wireless Networking","publication_year":2026,"publication_date":"2026-04-03","ids":{"openalex":"https://openalex.org/W7154258561","doi":"https://doi.org/10.48550/arxiv.2604.09680"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09680","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09680","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09680","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064365861","display_name":"Haiyun Liu","orcid":"https://orcid.org/0000-0002-7234-5636"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Haiyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076313927","display_name":"Jiahao Xue","orcid":"https://orcid.org/0000-0001-6303-4257"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Jiahao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133568943","display_name":"Jie Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133623313","display_name":"Yao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100312013","display_name":"Zhuo L\u00fc","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Zhuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.7651000022888184,"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":0.7651000022888184,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.04190000146627426,"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":0.03269999846816063,"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/server","display_name":"Server","score":0.7023000121116638},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6288999915122986},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.603600025177002},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.590499997138977},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5421000123023987},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.5212000012397766},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5078999996185303},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.5041999816894531}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8238000273704529},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.7023000121116638},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6288999915122986},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.6108999848365784},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.603600025177002},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.590499997138977},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.5586000084877014},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5421000123023987},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.5212000012397766},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.5041999816894531},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.4869999885559082},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4794999957084656},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4675000011920929},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.43619999289512634},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2694999873638153}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09680","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09680","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09680","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09680","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Today's":[0],"5G":[1],"and":[2,15,83,132,170,188,219,228],"NextG":[3,229],"wireless":[4,230],"networks":[5,70],"are":[6],"moving":[7],"toward":[8],"using":[9,62],"the":[10,42,63,74,77,162,185,192,208],"coordinated":[11],"multi-point":[12],"(CoMP)":[13],"transmission":[14],"reception":[16],"technique,":[17],"where":[18],"a":[19,57,138,144,217],"client":[20,46],"can":[21,47,195],"be":[22,48],"simultaneously":[23,110],"served":[24],"by":[25,181],"multiple":[26,113,198],"base":[27],"stations":[28],"(BSs)":[29],"for":[30,71,86,117,222],"better":[31],"communication":[32],"performance.":[33],"However,":[34],"traditional":[35,64,158],"hierarchical":[36,69,99],"federated":[37,100],"learning":[38,101],"(HFL)":[39],"architectures":[40,66],"impose":[41],"constraint":[43],"that":[44,155,214],"each":[45,177],"associated":[49],"with":[50,112,143],"only":[51,182],"one":[52],"edge":[53,114],"server":[54],"(ES)":[55],"at":[56],"time.":[58],"If":[59],"we":[60,96],"keep":[61],"HFL":[65],"in":[67,89,106,226],"modern":[68],"model":[72,118,130,224],"training,":[73],"benefits":[75],"of":[76,184,191],"CoMP":[78],"technique":[79],"would":[80],"remain":[81],"unexploited":[82],"leave":[84],"room":[85],"further":[87],"improvements":[88],"training":[90,134,225],"efficiency.":[91,135],"To":[92],"address":[93],"this":[94],"issue,":[95],"propose":[97],"hybrid":[98],"(HHFL),":[102],"which":[103],"allows":[104],"clients":[105,194],"overlapping":[107],"regions":[108],"to":[109,123,148,197,203],"communicate":[111],"servers":[115],"(ESs)":[116],"aggregation.":[119],"HHFL":[120,156,200,215],"is":[121,167,179],"able":[122],"enhance":[124],"inter-ES":[125],"knowledge":[126],"sharing,":[127],"thereby":[128],"mitigating":[129],"divergence":[131],"improving":[133],"We":[136],"provide":[137],"rigorous":[139],"theoretical":[140],"convergence":[141,145,206],"analysis":[142],"upper":[146],"bound":[147],"validate":[149],"its":[150],"effectiveness.":[151],"Experimental":[152],"results":[153,212],"show":[154],"outperforms":[157],"HFL,":[159],"particularly":[160],"when":[161,176],"data":[163],"across":[164],"different":[165],"ESs":[166],"not":[168],"independent":[169],"identically":[171],"distributed":[172],"(non-IID).":[173],"For":[174],"example,":[175],"ES":[178],"dominated":[180],"two":[183],"ten":[186],"classes":[187],"15":[189],"out":[190],"57":[193],"connect":[196],"ESs,":[199],"achieves":[201],"up":[202],"2x":[204],"faster":[205],"under":[207],"same":[209],"configuration.":[210],"These":[211],"demonstrate":[213],"provides":[216],"scalable":[218],"efficient":[220],"solution":[221],"FL":[223],"today's":[227],"networks.":[231]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-15T00:00:00"}
