{"id":"https://openalex.org/W7220714846","doi":"https://doi.org/10.1109/pimrc69400.2026.11711957","title":"QuantFL: Pre-Training-Aware Update Quantisation for Communication-Efficient Federated Learning in the 6G IoT-Edge-Cloud Continuum","display_name":"QuantFL: Pre-Training-Aware Update Quantisation for Communication-Efficient Federated Learning in the 6G IoT-Edge-Cloud Continuum","publication_year":2026,"publication_date":"2026-09-01","ids":{"openalex":"https://openalex.org/W7220714846","doi":"https://doi.org/10.1109/pimrc69400.2026.11711957"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc69400.2026.11711957","doi":"https://doi.org/10.1109/pimrc69400.2026.11711957","is_oa":true,"landing_page_url":"https://doi.org/10.1109/pimrc69400.2026.11711957","pdf_url":null,"source":{"id":"https://openalex.org/S4363605306","display_name":"IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 37th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/pimrc69400.2026.11711957","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026556562","display_name":"Charuka Herath","orcid":"https://orcid.org/0009-0009-1369-0120","observed_orcids":["https://orcid.org/0009-0009-1369-0120"]},"institutions":[{"id":"https://openalex.org/I143804889","display_name":"Loughborough University","ror":"https://ror.org/04vg4w365","country_code":"GB","type":"education","lineage":["https://openalex.org/I143804889"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Charuka Herath","raw_affiliation_strings":["Institute for Digital Technologies Loughborough University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Digital Technologies Loughborough University","institution_ids":["https://openalex.org/I143804889"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021724967","display_name":"Yogachandran Rahulamathavan","orcid":"https://orcid.org/0000-0002-1722-8621","observed_orcids":["https://orcid.org/0000-0002-1722-8621"]},"institutions":[{"id":"https://openalex.org/I143804889","display_name":"Loughborough University","ror":"https://ror.org/04vg4w365","country_code":"GB","type":"education","lineage":["https://openalex.org/I143804889"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yogachandran Rahulamathavan","raw_affiliation_strings":["Institute for Digital Technologies Loughborough University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Digital Technologies Loughborough University","institution_ids":["https://openalex.org/I143804889"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123083554","display_name":"Varuna De Silva","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I143804889","display_name":"Loughborough University","ror":"https://ror.org/04vg4w365","country_code":"GB","type":"education","lineage":["https://openalex.org/I143804889"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Varuna De Silva","raw_affiliation_strings":["Institute for Digital Technologies Loughborough University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Digital Technologies Loughborough University","institution_ids":["https://openalex.org/I143804889"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009232291","display_name":"Sangarapillai Lambotharan","orcid":"https://orcid.org/0000-0001-5255-7036","observed_orcids":["https://orcid.org/0000-0001-5255-7036"]},"institutions":[{"id":"https://openalex.org/I143804889","display_name":"Loughborough University","ror":"https://ror.org/04vg4w365","country_code":"GB","type":"education","lineage":["https://openalex.org/I143804889"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sangarapillai Lambotharan","raw_affiliation_strings":["Institute for Digital Technologies Loughborough University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Digital Technologies Loughborough University","institution_ids":["https://openalex.org/I143804889"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143804889"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.67324065,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9907000064849854,"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":0.9907000064849854,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0026000000070780516,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.002099999925121665,"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/federated-learning","display_name":"federated learning","score":0.9399999976158142},{"id":"https://openalex.org/keywords/communication-efficiency","display_name":"communication efficiency","score":0.6919999718666077},{"id":"https://openalex.org/keywords/pretraining","display_name":"pre-training","score":0.5820000171661377},{"id":"https://openalex.org/keywords/codebook","display_name":"codebook","score":0.44200000166893005},{"id":"https://openalex.org/keywords/6g-networks","display_name":"6G","score":0.6439999938011169},{"id":"https://openalex.org/keywords/non-iid-data","display_name":"non-IID data","score":0.781000018119812},{"id":"https://openalex.org/keywords/error-feedback","display_name":"error feedback","score":0.7860000133514404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6238999962806702},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4323999881744385},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3668000102043152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33889999985694885},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3174000084400177},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.2827000021934509},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc69400.2026.11711957","doi":"https://doi.org/10.1109/pimrc69400.2026.11711957","is_oa":true,"landing_page_url":"https://doi.org/10.1109/pimrc69400.2026.11711957","pdf_url":null,"source":{"id":"https://openalex.org/S4363605306","display_name":"IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 37th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/pimrc69400.2026.11711957","doi":"https://doi.org/10.1109/pimrc69400.2026.11711957","is_oa":true,"landing_page_url":"https://doi.org/10.1109/pimrc69400.2026.11711957","pdf_url":null,"source":{"id":"https://openalex.org/S4363605306","display_name":"IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 37th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4943999946117401,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2541884796","https://openalex.org/W2996979369","https://openalex.org/W3021654819","https://openalex.org/W3137147200","https://openalex.org/W4409185463","https://openalex.org/W4409475340","https://openalex.org/W4414648333","https://openalex.org/W4415796518","https://openalex.org/W7133192773"],"related_works":["https://openalex.org/W7138918205","https://openalex.org/W7212125195","https://openalex.org/W4391941907","https://openalex.org/W7171625074","https://openalex.org/W7204257553","https://openalex.org/W7203742245","https://openalex.org/W7172445151","https://openalex.org/W7141555508","https://openalex.org/W7153311845","https://openalex.org/W7164561072"],"abstract_inverted_index":{"Future":[0],"6G":[1],"IoT-edge-cloud":[2],"systems":[3],"will":[4],"rely":[5],"on":[6,127,159],"distributed":[7],"intelligence,":[8],"where":[9],"edge":[10,169,188],"devices":[11],"adapt":[12],"shared":[13],"models":[14],"using":[15,59],"local":[16,76],"private":[17],"data.":[18,133],"Federated":[19],"learning":[20],"(FL)":[21],"supports":[22],"this":[23],"setting,":[24],"but":[25],"repeated":[26],"transmission":[27],"of":[28,75,88],"full-precision":[29],"model":[30],"updates":[31,58],"remains":[32,152],"expensive":[33],"over":[34],"bandwidth-limited":[35],"and":[36,54,73,108,118,124,129,155,178],"energy-constrained":[37],"wireless":[38,168],"links.":[39],"This":[40],"paper":[41],"presents":[42],"QuantFL,":[43],"a":[44,51,85,182],"communication-efficient":[45],"FL":[46],"framework":[47],"that":[48,67],"starts":[49],"from":[50],"pretrained":[52],"initialisation":[53],"compresses":[55],"per-layer":[56],"client":[57],"bucket-based":[60],"scalar":[61,80],"quantisation.":[62],"The":[63],"key":[64],"observation":[65],"is":[66,163],"pre-training":[68],"reduces":[69],"the":[70,111,136,150,160,165],"dynamic":[71],"range":[72],"variance":[74],"updates,":[77],"making":[78],"simple":[79],"quantisation":[81],"more":[82],"effective":[83],"at":[84],"fixed":[86],"number":[87],"code":[89],"levels.":[90],"Clients":[91],"transmit":[92],"compact":[93],"bucket":[94,102],"indices":[95],"every":[96],"round,":[97],"while":[98],"codebooks,":[99],"defined":[100],"as":[101,181],"boundary":[103],"lists,":[104],"are":[105],"refreshed":[106],"infrequently":[107],"amortised":[109],"in":[110,167],"communication":[112],"budget.":[113],"We":[114,171],"evaluate":[115],"Bucket-Uniform":[116],"(BU)":[117],"Bucket-Quantile":[119],"(BQ)":[120],"quantisers":[121],"against":[122],"QSGD":[123],"non-quantised":[125],"FedAvg":[126],"MNIST":[128],"CIFAR-100":[130],"under":[131],"non-IID":[132],"BU":[134],"provides":[135],"strongest":[137],"accuracy-communication":[138],"tradeoff,":[139],"achieving":[140],"competitive":[141],"accuracy":[142],"with":[143,175],"approximately":[144],"40%":[145],"total":[146],"uplink+downlink":[147],"reduction":[148],"when":[149],"downlink":[151],"full":[153],"precision":[154],"substantially":[156],"larger":[157],"savings":[158],"uplink,":[161],"which":[162],"often":[164],"bottleneck":[166],"learning.":[170],"further":[172],"discuss":[173],"compatibility":[174],"error":[176],"feedback":[177],"position":[179],"QuantFL":[180],"lightweight":[183],"update-compression":[184],"primitive":[185],"for":[186],"scalable":[187],"intelligence.":[189]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-10-07T00:00:00"}