{"id":"https://openalex.org/W4385805144","doi":"https://doi.org/10.1109/vtc2023-spring57618.2023.10199491","title":"A Federated Channel Modeling System using Generative Neural Networks","display_name":"A Federated Channel Modeling System using Generative Neural Networks","publication_year":2023,"publication_date":"2023-06-01","ids":{"openalex":"https://openalex.org/W4385805144","doi":"https://doi.org/10.1109/vtc2023-spring57618.2023.10199491"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2023-spring57618.2023.10199491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2023-spring57618.2023.10199491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://openportal.isti.cnr.it/doc?id=people______::0ecac2366bb24cf71e958141873d049a","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060609702","display_name":"Saira Bano","orcid":"https://orcid.org/0000-0001-8126-4638"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]},{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Saira Bano","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy","Information Science and Technology Institute \"A. Faedo\", National Research Council, Pisa, Italy","Department of Information Engineering, University of Pisa, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy","institution_ids":["https://openalex.org/I108290504"]},{"raw_affiliation_string":"Information Science and Technology Institute \"A. Faedo\", National Research Council, Pisa, Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"raw_affiliation_string":"Department of Information Engineering, University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091257734","display_name":"Pietro Cassar\u00e1","orcid":"https://orcid.org/0000-0002-3704-4133"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Pietro Cassar\u00e0","raw_affiliation_strings":["National Research Council,Information Science and Technology Institute \"A. Faedo\",Pisa,Italy","Information Science and Technology Institute \"A. Faedo\", National Research Council, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Research Council,Information Science and Technology Institute \"A. Faedo\",Pisa,Italy","institution_ids":["https://openalex.org/I122991210"]},{"raw_affiliation_string":"Information Science and Technology Institute \"A. Faedo\", National Research Council, Pisa, Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018894843","display_name":"Nicola Tonellotto","orcid":"https://orcid.org/0000-0002-7427-1001"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicola Tonellotto","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy","Department of Information Engineering, University of Pisa, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy","institution_ids":["https://openalex.org/I108290504"]},{"raw_affiliation_string":"Department of Information Engineering, University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048540584","display_name":"Alberto Gotta","orcid":"https://orcid.org/0000-0002-8134-7844"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alberto Gotta","raw_affiliation_strings":["National Research Council,Information Science and Technology Institute \"A. Faedo\",Pisa,Italy","Information Science and Technology Institute \"A. Faedo\", National Research Council, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Research Council,Information Science and Technology Institute \"A. Faedo\",Pisa,Italy","institution_ids":["https://openalex.org/I122991210"]},{"raw_affiliation_string":"Information Science and Technology Institute \"A. Faedo\", National Research Council, Pisa, Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3484,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57312094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9987000226974487,"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/T13121","display_name":"Radio Wave Propagation Studies","score":0.9538999795913696,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11234","display_name":"Precipitation Measurement and Analysis","score":0.9506999850273132,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7585030794143677},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7469965815544128},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.6290354132652283},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6205050945281982},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6057471036911011},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.48947012424468994},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4891848862171173},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4857838451862335},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.47231125831604004},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46193161606788635},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4339603781700134},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4031326174736023},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3229401707649231},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10215127468109131}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7585030794143677},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7469965815544128},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.6290354132652283},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6205050945281982},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6057471036911011},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.48947012424468994},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4891848862171173},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4857838451862335},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.47231125831604004},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46193161606788635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4339603781700134},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4031326174736023},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3229401707649231},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10215127468109131},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/vtc2023-spring57618.2023.10199491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2023-spring57618.2023.10199491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)","raw_type":"proceedings-article"},{"id":"pmh:oai:arpi.unipi.it:11568/1205589","is_oa":false,"landing_page_url":"https://hdl.handle.net/11568/1205589","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:dnet:people______::0ecac2366bb24cf71e958141873d049a","is_oa":true,"landing_page_url":"https://openportal.isti.cnr.it/doc?id=people______::0ecac2366bb24cf71e958141873d049a","pdf_url":null,"source":{"id":"https://openalex.org/S7407055261","display_name":"ISTI Open Portal","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"VTC2023-Spring - IEEE 97th Vehicular Technology Conference, Florence, Italy, 20-23/06/2023","raw_type":"http://purl.org/coar/resource_type/c_5794"}],"best_oa_location":{"id":"pmh:oai:dnet:people______::0ecac2366bb24cf71e958141873d049a","is_oa":true,"landing_page_url":"https://openportal.isti.cnr.it/doc?id=people______::0ecac2366bb24cf71e958141873d049a","pdf_url":null,"source":{"id":"https://openalex.org/S7407055261","display_name":"ISTI Open Portal","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"VTC2023-Spring - IEEE 97th Vehicular Technology Conference, Florence, Italy, 20-23/06/2023","raw_type":"http://purl.org/coar/resource_type/c_5794"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W2022276843","https://openalex.org/W2058045633","https://openalex.org/W2125389028","https://openalex.org/W3013523550","https://openalex.org/W3037170119","https://openalex.org/W3096831136","https://openalex.org/W3112014495","https://openalex.org/W3124073676","https://openalex.org/W3135006098","https://openalex.org/W3179283102","https://openalex.org/W4211120851","https://openalex.org/W4281943365","https://openalex.org/W4318619660","https://openalex.org/W6640963894","https://openalex.org/W6678815747","https://openalex.org/W6728757088","https://openalex.org/W6789981794"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4309969736","https://openalex.org/W4394785709","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W2770818364","https://openalex.org/W2953501176","https://openalex.org/W2965095304","https://openalex.org/W2470043383"],"abstract_inverted_index":{"The":[0,162],"paper":[1],"proposes":[2],"a":[3,11,38,57,61,79],"data-driven":[4,195],"approach":[5,192],"to":[6,28,76],"air-to-ground":[7,53],"channel":[8,47,196],"estimation":[9,48],"in":[10,179,193,202],"millimeter-wave":[12],"wireless":[13],"network":[14],"on":[15],"an":[16],"unmanned":[17],"aerial":[18],"vehicle.":[19],"Unlike":[20],"traditional":[21],"centralized":[22],"learning":[23],"methods":[24],"that":[25,41,83,168,198],"are":[26],"specific":[27],"certain":[29],"geographical":[30],"areas":[31],"and":[32,49,60,91,124,136,156,159],"inappropriate":[33],"for":[34,46],"others,":[35],"we":[36,116],"propose":[37],"generalized":[39],"model":[40,82,135],"uses":[42],"Federated":[43],"Learning":[44],"(FL)":[45],"can":[50,84,199],"predict":[51],"the":[52,96,105,110,113,128,134,137,144,165,169,176,182,187,190],"path":[54],"loss":[55],"between":[56,127],"low-altitude":[58],"platform":[59],"terrestrial":[62],"terminal.":[63],"To":[64,108],"this":[65],"end,":[66],"our":[67],"proposed":[68,114,145,191],"FL-based":[69],"Generative":[70],"Adversarial":[71],"Network":[72],"(FL-GAN)":[73],"is":[74],"designed":[75],"function":[77],"as":[78,152],"generative":[80,149],"data":[81,89,102,130,139,171],"learn":[85],"different":[86,203],"types":[87],"of":[88,112,164,189],"distributions":[90,98],"generate":[92],"realistic":[93],"patterns":[94],"from":[95],"same":[97],"without":[99],"requiring":[100],"prior":[101],"analysis":[103],"before":[104],"training":[106],"phase.":[107],"evaluate":[109,117],"effectiveness":[111,188],"model,":[115],"its":[118],"performance":[119],"using":[120],"Kullback-Leibler":[121],"divergence":[122],"(KL),":[123],"Wasserstein":[125],"distance":[126],"synthetic":[129,170],"distribution":[131,180],"generated":[132,172],"by":[133,173],"actual":[138],"distribution.":[140],"We":[141],"also":[142],"compare":[143],"technique":[146],"with":[147,181],"other":[148],"models,":[150],"such":[151],"FL-Variational":[153],"Autoencoder":[154],"(FL-VAE)":[155],"stand-alone":[157],"VAE":[158],"GAN":[160],"models.":[161],"results":[163],"study":[166],"show":[167],"FL-GAN":[174],"has":[175],"highest":[177],"similarity":[178],"real":[183],"data.":[184],"This":[185],"shows":[186],"generating":[194],"models":[197],"be":[200],"used":[201],"regions.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}