{"id":"https://openalex.org/W4226363234","doi":"https://doi.org/10.1109/lcomm.2022.3170211","title":"A Privacy-Preserved Split Learning Solution for Deep Learning-Based mmWave Beam Selection","display_name":"A Privacy-Preserved Split Learning Solution for Deep Learning-Based mmWave Beam Selection","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4226363234","doi":"https://doi.org/10.1109/lcomm.2022.3170211"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2022.3170211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2022.3170211","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-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/A5056820584","display_name":"Muchen Tian","orcid":"https://orcid.org/0000-0002-5335-2187"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muchen Tian","raw_affiliation_strings":["National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","Purple Mountain Laboratories, Pervasive Communications Center, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5335-2187","affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Pervasive Communications Center, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019360899","display_name":"Zhengming Zhang","orcid":"https://orcid.org/0000-0003-3096-1286"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengming Zhang","raw_affiliation_strings":["National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","Purple Mountain Laboratories, Pervasive Communications Center, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-3096-1286","affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Pervasive Communications Center, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100948211","display_name":"Qinzhen Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinzhen Xu","raw_affiliation_strings":["National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","Purple Mountain Laboratories, Pervasive Communications Center, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Pervasive Communications Center, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045457613","display_name":"L\u00fcxi Yang","orcid":"https://orcid.org/0000-0003-1474-1806"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luxi Yang","raw_affiliation_strings":["National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","Purple Mountain Laboratories, Pervasive Communications Center, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-1474-1806","affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Pervasive Communications Center, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8835,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.71317564,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"26","issue":"7","first_page":"1474","last_page":"1478"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9825999736785889,"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/T10752","display_name":"Terahertz technology and applications","score":0.9782999753952026,"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/computer-science","display_name":"Computer science","score":0.8578633666038513},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.7189764976501465},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.649965763092041},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6200484037399292},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6147432327270508},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5351202487945557},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49851107597351074},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4899255633354187},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.4659615159034729},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.4658048748970032},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.43522652983665466},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.42458346486091614},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4119637906551361},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4072212874889374},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.10881224274635315},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08797886967658997}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8578633666038513},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.7189764976501465},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.649965763092041},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6200484037399292},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6147432327270508},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5351202487945557},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49851107597351074},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4899255633354187},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.4659615159034729},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.4658048748970032},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.43522652983665466},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.42458346486091614},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4119637906551361},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4072212874889374},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10881224274635315},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08797886967658997},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2022.3170211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2022.3170211","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3630466707","display_name":null,"funder_award_id":"U1936201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8475670238","display_name":"\u6df1\u5ea6\u5b66\u4e60\u8f85\u52a9\u7684\u667a\u80fd\u65e0\u7ebf\u901a\u4fe1\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2027595342","https://openalex.org/W2132211083","https://openalex.org/W2593066675","https://openalex.org/W2603407422","https://openalex.org/W2614851539","https://openalex.org/W2622263826","https://openalex.org/W2913861122","https://openalex.org/W2914111477","https://openalex.org/W2963209930","https://openalex.org/W2972570881","https://openalex.org/W3009048827","https://openalex.org/W3039059058","https://openalex.org/W3047556258","https://openalex.org/W3098782124","https://openalex.org/W3141585064","https://openalex.org/W3186724161","https://openalex.org/W6637373629","https://openalex.org/W6728757088","https://openalex.org/W6739622702","https://openalex.org/W6760184523","https://openalex.org/W6767676916"],"related_works":["https://openalex.org/W2944823289","https://openalex.org/W3037018281","https://openalex.org/W2003209439","https://openalex.org/W4321854979","https://openalex.org/W2358319515","https://openalex.org/W2972592048","https://openalex.org/W4312214821","https://openalex.org/W2497626292","https://openalex.org/W2390344072","https://openalex.org/W2972511296"],"abstract_inverted_index":{"Side":[0],"information,":[1],"like":[2],"light":[3],"detection":[4],"and":[5,27,62,78,100],"ranging":[6],"data,":[7],"is":[8,57],"promising":[9],"to":[10,73,80],"help":[11],"the":[12,48,54,68,90,97],"millimeter":[13],"wave":[14],"(mmWave)":[15],"system":[16],"achieve":[17],"efficient":[18],"link":[19],"configuration":[20],"through":[21],"machine":[22],"learning":[23,44],"methods.":[24],"However,":[25],"collecting":[26],"using":[28],"this":[29,36],"information":[30],"may":[31],"violate":[32],"user":[33],"privacy.":[34],"In":[35,64],"letter,":[37],"we":[38],"propose":[39],"a":[40,104],"novel":[41],"privacy-preserved":[42],"split":[43],"(SL)":[45],"solution":[46],"for":[47],"beam":[49],"selection":[50],"problem,":[51],"in":[52,103],"which":[53],"raw":[55],"data":[56],"not":[58],"uploaded":[59],"during":[60],"training":[61],"inference.":[63],"particular,":[65],"it":[66],"uses":[67],"proposed":[69,91],"feature":[70],"mix":[71],"method":[72,92],"get":[74],"better":[75],"generalization":[76],"performance":[77],"robustness":[79],"non-independently":[81],"identically":[82],"distribution":[83],"(non-iid)":[84],"data.":[85],"Extensive":[86],"experiments":[87],"demonstrate":[88],"that":[89],"outperforms":[93],"learning-based":[94],"baselines":[95],"(e.g.":[96],"original":[98],"SL":[99],"federated":[101],"learning)":[102],"variety":[105],"of":[106],"settings.":[107]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
