{"id":"https://openalex.org/W2911269749","doi":null,"title":"Low-Latency Broadband Analog Aggregation for Federated Edge Learning.","display_name":"Low-Latency Broadband Analog Aggregation for Federated Edge Learning.","publication_year":2018,"publication_date":"2018-12-30","ids":{"openalex":"https://openalex.org/W2911269749","mag":"2911269749"},"language":"en","primary_location":{"id":"mag:2911269749","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1812.11494v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/1812.11494v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004583148","display_name":"Guangxu Zhu","orcid":"https://orcid.org/0000-0001-9532-9201","observed_orcids":["https://orcid.org/0000-0001-9532-9201"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guangxu Zhu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9532-9201","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424530","display_name":"Yong Wang","orcid":"https://orcid.org/0000-0003-2006-5410","observed_orcids":["https://orcid.org/0000-0003-2006-5410"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong Wang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2006-5410","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5007131492","display_name":"Kaibin Huang","orcid":"https://orcid.org/0000-0001-8773-4629","observed_orcids":["https://orcid.org/0000-0001-8773-4629"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaibin Huang","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":43,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.5536999702453613,"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":0.5536999702453613,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.259799987077713,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.015599999576807022,"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/federated-edge-learning","display_name":"federated edge learning","score":0.996999979019165},{"id":"https://openalex.org/keywords/over-the-air-aggregation","display_name":"over-the-air aggregation","score":0.843999981880188},{"id":"https://openalex.org/keywords/multiple-access-channel","display_name":"multiple access channel","score":0.8169999718666077},{"id":"https://openalex.org/keywords/communication-latency-reduction","display_name":"communication latency reduction","score":0.7559999823570251},{"id":"https://openalex.org/keywords/interference-exploitation","display_name":"interference exploitation","score":0.39800000190734863},{"id":"https://openalex.org/keywords/opportunistic-scheduling","display_name":"opportunistic scheduling","score":0.9629999995231628},{"id":"https://openalex.org/keywords/ofdma-comparison","display_name":"OFDMA comparison","score":0.7070000171661377},{"id":"https://openalex.org/keywords/device-mobility","display_name":"device mobility","score":0.6470000147819519},{"id":"https://openalex.org/keywords/on-device-learning","display_name":"on-device learning","score":0.5929999947547913}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8232632875442505},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.6623444557189941},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.48979783058166504},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4891681969165802},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.4868004024028778},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4743056297302246},{"id":"https://openalex.org/C509933004","wikidata":"https://www.wikidata.org/wiki/Q194163","display_name":"Broadband","level":2,"score":0.47228866815567017},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.4503277540206909},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.44808027148246765},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4275904595851898},{"id":"https://openalex.org/C78834623","wikidata":"https://www.wikidata.org/wiki/Q640394","display_name":"Mobile broadband","level":3,"score":0.4215741455554962},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3808578848838806},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.24807175993919373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20921695232391357},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1488417387008667},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.12358877062797546},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.11624425649642944},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.10888364911079407},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2911269749","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1812.11494v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:2911269749","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1812.11494v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1561389464","https://openalex.org/W1561759234","https://openalex.org/W2005196269","https://openalex.org/W2025603103","https://openalex.org/W2035266863","https://openalex.org/W2079836048","https://openalex.org/W2083632855","https://openalex.org/W2100359132","https://openalex.org/W2128011496","https://openalex.org/W2139787801","https://openalex.org/W2140227342","https://openalex.org/W2149463165","https://openalex.org/W2172236196","https://openalex.org/W2336650964","https://openalex.org/W2541884796","https://openalex.org/W2565448914","https://openalex.org/W2624989916","https://openalex.org/W2741736887","https://openalex.org/W2793925626","https://openalex.org/W2861117319","https://openalex.org/W2869726119","https://openalex.org/W2969750416","https://openalex.org/W3004277316","https://openalex.org/W3101036738"],"related_works":["https://openalex.org/W2907943746","https://openalex.org/W2944099577","https://openalex.org/W3108590825","https://openalex.org/W3123206626","https://openalex.org/W4392152687","https://openalex.org/W3199037570","https://openalex.org/W3212864330","https://openalex.org/W4283207041","https://openalex.org/W2964169433","https://openalex.org/W7172346466"],"abstract_inverted_index":{"The":[0],"popularity":[1],"of":[2,9,65,134,146,169,208,237,245,263],"mobile":[3,50],"devices":[4,120,184,217],"results":[5,151],"in":[6,152,234],"the":[7,16,21,41,58,63,131,147,158,167,197,200,206,235,242,246,251,260,264],"availability":[8],"enormous":[10],"data":[11,22],"and":[12,23,46,98,199,250],"computational":[13],"resources":[14],"at":[15,40],"network":[17],"edge.":[18],"To":[19,69],"leverage":[20],"resources,":[24],"a":[25,79,89,105,135,174,189,219],"new":[26],"machine":[27],"learning":[28,36,94,100,232],"paradigm,":[29],"called":[30],"edge":[31,42,67,85,93],"learning,":[32],"has":[33],"emerged":[34],"where":[35,96],"algorithms":[37],"are":[38,55,101,254],"deployed":[39],"for":[43,84,187,213],"providing":[44],"fast":[45,66,144],"intelligent":[47],"services":[48],"to":[49,103,142,180,194,229,268],"users.":[51],"While":[52],"computing":[53],"speeds":[54],"advancing":[56],"rapidly,":[57],"communication":[59],"latency":[60,81,154,244,261],"is":[61,75,112,140,171,192,224,266],"becoming":[62],"bottleneck":[64],"learning.":[68,86],"address":[70],"this":[71,73,165],"issue,":[72],"work":[74],"focused":[76],"on":[77],"designing":[78],"low":[80],"multi-access":[82,136,243],"scheme":[83,212,223,253],"We":[87],"consider":[88],"popular":[90],"framework,":[91],"federated":[92],"(FEEL),":[95],"edge-server":[97],"on-device":[99],"synchronized":[102],"train":[104],"model":[106,115,148],"without":[107],"violating":[108],"user-data":[109],"privacy.":[110],"It":[111],"proposed":[113,247],"that":[114,215],"updates":[116],"simultaneously":[117],"transmitted":[118],"by":[119,129],"over":[121],"broadband":[122],"channels":[123],"should":[124],"be":[125],"analog":[126,248],"aggregated":[127],"over-the-air":[128],"exploiting":[130],"superposition":[132],"property":[133],"channel.":[137],"Thereby,":[138],"interference":[139],"harnessed":[141],"provide":[143],"implementation":[145],"aggregation.":[149],"This":[150,204,222],"dramatical":[153],"reduction":[155,262],"compared":[156],"with":[157,272],"traditional":[159],"orthogonal":[160],"access":[161],"(i.e.,":[162],"OFDMA).":[163],"In":[164],"work,":[166],"performance":[168,233],"FEEL":[170,214],"characterized":[172],"targeting":[173],"single-cell":[175],"random":[176],"network.":[177],"First,":[178],"due":[179],"power":[181],"alignment":[182],"between":[183,196],"as":[185],"required":[186],"aggregation,":[188],"fundamental":[190],"tradeoff":[191],"shown":[193,225],"exist":[195],"update-reliability":[198],"expected":[201],"update-truncation":[202],"ratio.":[203],"motivates":[205],"design":[207],"an":[209],"opportunistic":[210],"scheduling":[211],"selects":[216],"within":[218],"distance":[220],"threshold.":[221],"using":[226],"real":[227],"datasets":[228],"yield":[230],"satisfactory":[231],"presence":[236],"high":[238],"mobility.":[239],"Second,":[240],"both":[241],"aggregation":[249],"OFDMA":[252],"analyzed.":[255],"Their":[256],"ratio,":[257],"which":[258],"quantifies":[259],"former,":[265],"proved":[267],"scale":[269],"almost":[270],"linearly":[271],"device":[273],"population.":[274]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2019-02-21T00:00:00"}
