{"id":"https://openalex.org/W7129662123","doi":"https://doi.org/10.1109/lsp.2026.3665655","title":"Generative Model-Aided Continual Learning for CSI Feedback in FDD mMIMO-OFDM Systems","display_name":"Generative Model-Aided Continual Learning for CSI Feedback in FDD mMIMO-OFDM Systems","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7129662123","doi":"https://doi.org/10.1109/lsp.2026.3665655"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2026.3665655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3665655","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal Processing 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/A5028566209","display_name":"G. M. Liu","orcid":"https://orcid.org/0009-0004-9608-6335"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guijun Liu","raw_affiliation_strings":["School of Information and Intelligent Science, Donghua University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-9608-6335","affiliations":[{"raw_affiliation_string":"School of Information and Intelligent Science, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126224239","display_name":"Yuwen Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwen Cao","raw_affiliation_strings":["School of Information and Intelligent Science, Donghua University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9486-4349","affiliations":[{"raw_affiliation_string":"School of Information and Intelligent Science, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126206064","display_name":"Tomoaki Ohtsuki","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoaki Ohtsuki","raw_affiliation_strings":["Department of Information and Computer Science, Keio University, Yokohama, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3961-1426","affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121991874","display_name":"Jiguang He","orcid":null},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiguang He","raw_affiliation_strings":["School of Computing and Information Technology, the Dongguan Key Laboratory for Intelligence and Information Technology, and the Great Bay Institute for Advanced Study, Great Bay University, Dongguan, China"],"raw_orcid":"https://orcid.org/0000-0002-6227-2138","affiliations":[{"raw_affiliation_string":"School of Computing and Information Technology, the Dongguan Key Laboratory for Intelligence and Information Technology, and the Great Bay Institute for Advanced Study, Great Bay University, Dongguan, China","institution_ids":["https://openalex.org/I2799850029"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121530571","display_name":"Shahid Mumtaz","orcid":null},"institutions":[{"id":"https://openalex.org/I52590639","display_name":"Nottingham Trent University","ror":"https://ror.org/04xyxjd90","country_code":"GB","type":"education","lineage":["https://openalex.org/I52590639"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shahid Mumtaz","raw_affiliation_strings":["Department of Engineering, Nottingham Trent University, Nottingham, U.K"],"raw_orcid":"https://orcid.org/0000-0001-6364-6149","affiliations":[{"raw_affiliation_string":"Department of Engineering, Nottingham Trent University, Nottingham, U.K","institution_ids":["https://openalex.org/I52590639"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16399954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"1013","last_page":"1017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.7159000039100647,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.7159000039100647,"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/T11873","display_name":"PAPR reduction in OFDM","score":0.06629999727010727,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.05770000070333481,"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/robustness","display_name":"Robustness (evolution)","score":0.7023000121116638},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.5511000156402588},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5117999911308289},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.46549999713897705},{"id":"https://openalex.org/keywords/multiplexing","display_name":"Multiplexing","score":0.44040000438690186},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.40540000796318054},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3919000029563904},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.37529999017715454},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.36390000581741333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8342999815940857},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7023000121116638},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.5511000156402588},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5117999911308289},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5008999705314636},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.46549999713897705},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.44040000438690186},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3919000029563904},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.3416999876499176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34040001034736633},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2985000014305115},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.296099990606308},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C2778156585","wikidata":"https://www.wikidata.org/wiki/Q174053","display_name":"Relay","level":3,"score":0.26030001044273376},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.2567000091075897},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.2565000057220459},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2026.3665655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3665655","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1053294086","display_name":null,"funder_award_id":"62301143","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"autoencoder":[1],"(DAE)":[2],"frameworks":[3],"have":[4],"demonstrated":[5],"their":[6],"effectiveness":[7],"in":[8,16],"reducing":[9],"channel":[10],"state":[11],"information":[12,72],"(CSI)":[13],"feedback":[14,30,152],"overhead":[15],"massive":[17],"multiple-input":[18],"multiple-output":[19],"(mMIMO)":[20],"orthogonal":[21],"frequency":[22],"division":[23],"multiplexing":[24],"(OFDM)":[25],"systems.":[26],"However,":[27],"existing":[28],"CSI":[29,47,94,151],"models":[31,68],"struggle":[32],"to":[33,35,51,57,61,69],"adapt":[34],"dynamic":[36],"environments":[37,54,111],"caused":[38],"by":[39],"user":[40],"mobility,":[41],"requiring":[42],"retraining":[43],"when":[44],"encountering":[45],"new":[46,71],"distributions.":[48],"Moreover,":[49],"returning":[50],"previously":[52,77],"encountered":[53],"often":[55],"leads":[56],"performance":[58,75,116],"degradation":[59],"due":[60],"catastrophic":[62],"forgetting.":[63,121],"Continual":[64],"learning":[65,91],"involves":[66],"enabling":[67],"incorporate":[70],"while":[73,137],"maintaining":[74,138],"on":[76],"learned":[78],"tasks.":[79],"To":[80],"address":[81],"these":[82],"challenges,":[83],"we":[84],"propose":[85],"a":[86,98,102],"generative":[87],"adversarial":[88],"network":[89],"(GAN)-based":[90],"approach":[92,128],"for":[93],"feedback.":[95],"By":[96],"using":[97],"GAN":[99],"generator":[100],"as":[101],"memory":[103,140],"unit,":[104],"our":[105],"method":[106],"preserves":[107],"knowledge":[108],"from":[109],"past":[110],"and":[112,157],"ensures":[113],"consistently":[114],"high":[115],"across":[117],"diverse":[118],"scenarios":[119],"without":[120],"Simulation":[122],"results":[123],"show":[124],"that":[125],"the":[126,130,134],"proposed":[127],"enhances":[129],"generalization":[131],"capability":[132],"of":[133],"DAE":[135],"framework":[136],"low":[139],"overhead.":[141],"Furthermore,":[142],"it":[143],"can":[144],"be":[145],"seamlessly":[146],"integrated":[147],"with":[148],"other":[149],"advanced":[150],"models,":[153],"highlighting":[154],"its":[155],"robustness":[156],"adaptability.":[158]},"counts_by_year":[],"updated_date":"2026-02-28T06:14:18.631764","created_date":"2026-02-18T00:00:00"}