{"id":"https://openalex.org/W4406266862","doi":"https://doi.org/10.1109/vtc2024-fall63153.2024.10757649","title":"Low Complexity CSI Feedback Method Using Reformer","display_name":"Low Complexity CSI Feedback Method Using Reformer","publication_year":2024,"publication_date":"2024-10-07","ids":{"openalex":"https://openalex.org/W4406266862","doi":"https://doi.org/10.1109/vtc2024-fall63153.2024.10757649"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2024-fall63153.2024.10757649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2024-fall63153.2024.10757649","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)","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/A5101896863","display_name":"Yuki Saito","orcid":"https://orcid.org/0000-0003-3909-0747"},"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":true,"raw_author_name":"Yuki Saito","raw_affiliation_strings":["Keio University,Graduate School of Science and Technology,Yokohama,Japan"],"affiliations":[{"raw_affiliation_string":"Keio University,Graduate School of Science and Technology,Yokohama,Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068994330","display_name":"Mondher Bouazizi","orcid":"https://orcid.org/0000-0001-7055-9318"},"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":"Mondher Bouazizi","raw_affiliation_strings":["Keio University,Faculty of Science and Technology,Yokohama,Japan"],"affiliations":[{"raw_affiliation_string":"Keio University,Faculty of Science and Technology,Yokohama,Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016337773","display_name":"Tomoaki Ohtsuki","orcid":"https://orcid.org/0000-0003-3961-1426"},"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":["Keio University,Faculty of Science and Technology,Yokohama,Japan"],"affiliations":[{"raw_affiliation_string":"Keio University,Faculty of Science and Technology,Yokohama,Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101896863"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22730655,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.33230000734329224,"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/T10320","display_name":"Neural Networks and Applications","score":0.33230000734329224,"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/computer-science","display_name":"Computer science","score":0.5847939252853394},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3985305726528168},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.1330154836177826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08534207940101624}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5847939252853394},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3985305726528168},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.1330154836177826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08534207940101624}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2024-fall63153.2024.10757649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2024-fall63153.2024.10757649","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"To":[0],"leverage":[1],"antenna":[2],"diversity":[3],"effectively":[4],"in":[5],"Massive":[6],"Multiple-Input":[7],"Multiple-Output":[8],"(MIMO)":[9],"systems,":[10],"Channel":[11],"State":[12],"Information":[13],"(CSI)":[14],"utilization":[15],"at":[16],"the":[17,42,125,129,136,157,177],"base":[18],"station":[19],"(BS)":[20],"is":[21,32],"crucial.":[22],"In":[23,84,111],"Frequency":[24],"Division":[25],"Duplexing":[26],"(FDD)":[27],"MIMO":[28],"setups,":[29],"downlink":[30],"CSI":[31,52,117,130,146,158,172,178],"acquired":[33],"by":[34,123,166],"user":[35],"equipment":[36],"(UE)":[37],"and":[38],"transmitted":[39],"back":[40],"to":[41,71,104,143,176],"BS.":[43],"However,":[44],"this":[45,73,85,112],"feedback":[46,118,131,159,179],"overhead":[47],"diminishes":[48],"communication":[49],"throughput,":[50],"necessitating":[51],"compression":[53,59,78],"technologies.":[54],"Methods":[55],"such":[56,64],"as":[57,65,89,93],"traditional":[58],"or":[60,80],"more":[61],"advanced":[62],"ones":[63],"Transformer-based":[66],"neural":[67],"networks":[68],"which":[69],"aim":[70],"address":[72],"issue":[74],"suffer":[75],"from":[76],"low":[77],"rates":[79],"high":[81],"computational":[82,109,151,164],"cost.":[83],"context,":[86],"Reformers":[87],"emerge":[88],"a":[90,101,116],"potential":[91],"solution":[92],"they":[94],"employ":[95],"Locality-Sensitive":[96],"Hashing":[97],"(LSH)":[98],"attention,":[99],"offering":[100],"comparable":[102,171],"accuracy":[103,148,174],"Transformers":[105],"but":[106],"with":[107,135],"reduced":[108],"demands.":[110],"paper,":[113],"we":[114,141],"propose":[115],"method":[119,132,160,180],"using":[120,133,161,181],"Reformer.":[121],"Specifically,":[122],"replacing":[124],"multi-head":[126],"attention":[127,138],"of":[128,139],"Transformer":[134],"LSH":[137],"Reformer,":[140],"aimed":[142],"achieve":[144],"similar":[145],"reconstruction":[147,173],"while":[149,169],"reducing":[150],"complexity.":[152],"Computer":[153],"simulations":[154],"confirm":[155],"that":[156],"Reformer":[162],"reduces":[163],"complexity":[165],"about":[167],"12%":[168],"achieving":[170],"compared":[175],"Transformer.":[182]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}