{"id":"https://openalex.org/W4401509584","doi":"https://doi.org/10.1109/iccworkshops59551.2024.10615736","title":"Network-first Separate Training with Raw Dataset Sharing: A Training Approach for AI/ML-Driven CSI Feedback","display_name":"Network-first Separate Training with Raw Dataset Sharing: A Training Approach for AI/ML-Driven CSI Feedback","publication_year":2024,"publication_date":"2024-06-09","ids":{"openalex":"https://openalex.org/W4401509584","doi":"https://doi.org/10.1109/iccworkshops59551.2024.10615736"},"language":"en","primary_location":{"id":"doi:10.1109/iccworkshops59551.2024.10615736","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccworkshops59551.2024.10615736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Communications Workshops (ICC Workshops)","raw_type":"proceedings-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/A5044202720","display_name":"Aakash Saini","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159457","display_name":"Nokia (Germany)","ror":"https://ror.org/05nh5td39","country_code":"DE","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210159457"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Aakash Saini","raw_affiliation_strings":["Nokia Standards,Munich,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Standards,Munich,Germany","institution_ids":["https://openalex.org/I4210159457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100623838","display_name":"Jee Hyun Kim","orcid":"https://orcid.org/0000-0002-1299-4300"},"institutions":[{"id":"https://openalex.org/I4210159457","display_name":"Nokia (Germany)","ror":"https://ror.org/05nh5td39","country_code":"DE","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210159457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jee Hyun Kim","raw_affiliation_strings":["Nokia Standards,Munich,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Standards,Munich,Germany","institution_ids":["https://openalex.org/I4210159457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111287831","display_name":"Amir Tehrani","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159457","display_name":"Nokia (Germany)","ror":"https://ror.org/05nh5td39","country_code":"DE","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210159457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Amir Ahmadian Tehrani","raw_affiliation_strings":["Nokia Standards,Munich,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Standards,Munich,Germany","institution_ids":["https://openalex.org/I4210159457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090349133","display_name":"Yunchou Xing","orcid":"https://orcid.org/0000-0003-0378-2696"},"institutions":[{"id":"https://openalex.org/I72090969","display_name":"Nokia (United States)","ror":"https://ror.org/038km2573","country_code":"US","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I72090969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunchou Xing","raw_affiliation_strings":["Nokia Standards,Naperville,IL,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Standards,Naperville,IL,USA","institution_ids":["https://openalex.org/I72090969"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050486496","display_name":"Wolfgang Gerstacker","orcid":"https://orcid.org/0000-0002-5656-7829"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wolfgang Gerstacker","raw_affiliation_strings":["Institute for Digital Communications, Friedrich-Alexande-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg,Erlangen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Digital Communications, Friedrich-Alexande-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg,Erlangen,Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5044202720"],"corresponding_institution_ids":["https://openalex.org/I4210159457"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14032716,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1950","last_page":"1955"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.8571000099182129,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.8571000099182129,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.8019999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.9130206108093262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7539075016975403},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5485107898712158},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5386080741882324},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5250812768936157},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4140506088733673}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.9130206108093262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7539075016975403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5485107898712158},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5386080741882324},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5250812768936157},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4140506088733673},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccworkshops59551.2024.10615736","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccworkshops59551.2024.10615736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Communications Workshops (ICC Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2624494617","https://openalex.org/W2886124254","https://openalex.org/W2889482795","https://openalex.org/W2914338909","https://openalex.org/W2963145597","https://openalex.org/W3043472726","https://openalex.org/W3096330798","https://openalex.org/W4210852766","https://openalex.org/W4290994016","https://openalex.org/W4312050602","https://openalex.org/W6784333009"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"This":[0],"study":[1],"explores":[2],"the":[3,30,39,73,107,117,143,163],"enhancement":[4,141],"of":[5,25,75],"channel":[6],"state":[7],"information":[8],"(CSI)":[9],"feedback":[10],"in":[11],"wireless":[12],"communication":[13],"systems":[14],"by":[15],"applying":[16],"artificial":[17],"intelligence/machine":[18],"learning":[19],"(AI/ML).":[20],"The":[21],"traditional":[22],"joint":[23,174],"training":[24,76,90,147,175],"an":[26,35],"AI":[27,36],"encoder":[28],"at":[29,38,154],"user":[31],"equipment":[32],"(UE)":[33],"and":[34,58,91,132,166],"decoder":[37,125],"network":[40],"(NW)":[41],"side":[42],"presents":[43],"several":[44],"challenges.":[45],"Jointly":[46],"trained":[47],"models":[48],"require":[49],"sharing":[50],"proprietary":[51],"information,":[52],"increase":[53],"vulnerability":[54],"to":[55,70,120,129,142,149],"adversarial":[56],"attacks,":[57],"are":[59],"less":[60],"suited":[61],"for":[62,101],"multi-user":[63],"or":[64],"multi-base":[65],"station":[66],"scenarios.":[67],"In":[68,134],"response":[69],"these":[71],"challenges,":[72],"approach":[74,109],"model":[77,126],"entities":[78],"independently":[79],"has":[80],"garnered":[81],"interest,":[82],"centring":[83],"on":[84],"two":[85],"primary":[86],"methods:":[87],"UE-first":[88,108,167],"separate":[89,146],"NW-first":[92,145,165],"sepa-rate":[93],"training.":[94],"Empirical":[95],"findings":[96],"from":[97],"Release":[98],"18":[99],"AI/ML":[100],"Air":[102],"Interface":[103],"studies":[104],"indicate":[105],"that":[106,161],"yields":[110],"better":[111],"performance.":[112],"However,":[113],"this":[114,136],"method":[115],"limits":[116],"network's":[118],"flexibility":[119],"accommodate":[121],"distinct":[122],"NW":[123],"-side":[124],"configurations":[127],"tailored":[128],"various":[130],"cells":[131],"sites.":[133],"response,":[135],"paper":[137],"intro-duces":[138],"a":[139],"novel":[140],"conventional":[144],"strategy":[148],"achieve":[150],"performance":[151],"gains,":[152],"particularly":[153],"low":[155],"quantizer":[156],"resolution.":[157],"Our":[158],"results":[159],"confirm":[160],"both":[162,172],"improved":[164],"strategies":[168],"deliver":[169],"comparable":[170],"performance,":[171],"nearing":[173],"benchmarks.":[176]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
