{"id":"https://openalex.org/W4226021198","doi":"https://doi.org/10.1109/lwc.2022.3157263","title":"CVLNet: A Complex-Valued Lightweight Network for CSI Feedback","display_name":"CVLNet: A Complex-Valued Lightweight Network for CSI Feedback","publication_year":2022,"publication_date":"2022-03-08","ids":{"openalex":"https://openalex.org/W4226021198","doi":"https://doi.org/10.1109/lwc.2022.3157263"},"language":"en","primary_location":{"id":"doi:10.1109/lwc.2022.3157263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2022.3157263","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"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 Wireless 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/A5101502584","display_name":"Haozhen Li","orcid":"https://orcid.org/0000-0003-2554-4218"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haozhen Li","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014860128","display_name":"Boyuan Zhang","orcid":"https://orcid.org/0000-0002-7831-6318"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyuan Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103072860","display_name":"Haoran Chang","orcid":"https://orcid.org/0000-0001-7637-9975"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Chang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086203841","display_name":"Xin Liang","orcid":"https://orcid.org/0000-0003-4306-9836"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Liang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018769767","display_name":"Xinyu Gu","orcid":"https://orcid.org/0000-0001-6762-7463"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Gu","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101502584"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":2.8965,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91891327,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":"5","first_page":"1092","last_page":"1096"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9993000030517578,"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":0.9993000030517578,"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/T12791","display_name":"Full-Duplex Wireless Communications","score":0.9990000128746033,"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/T13905","display_name":"Telecommunications and Broadcasting Technologies","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.8018952012062073},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7441802024841309},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.6730359792709351},{"id":"https://openalex.org/keywords/telecommunications-link","display_name":"Telecommunications link","score":0.6231386065483093},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5678228735923767},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5364746451377869},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5185176134109497},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48765814304351807},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4370253384113312},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.16386261582374573},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1497175097465515}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8018952012062073},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7441802024841309},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.6730359792709351},{"id":"https://openalex.org/C138660444","wikidata":"https://www.wikidata.org/wiki/Q5607897","display_name":"Telecommunications link","level":2,"score":0.6231386065483093},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5678228735923767},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5364746451377869},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5185176134109497},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48765814304351807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4370253384113312},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.16386261582374573},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1497175097465515},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lwc.2022.3157263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2022.3157263","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"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 Wireless Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2072079297","https://openalex.org/W2279098554","https://openalex.org/W2903226808","https://openalex.org/W2963145597","https://openalex.org/W2964005248","https://openalex.org/W3045610411","https://openalex.org/W3089739838","https://openalex.org/W3134784220","https://openalex.org/W3158675441","https://openalex.org/W3164665065","https://openalex.org/W3170853162","https://openalex.org/W3183856285","https://openalex.org/W3203258883","https://openalex.org/W6695314431","https://openalex.org/W6738884980","https://openalex.org/W6757040593"],"related_works":["https://openalex.org/W4291722335","https://openalex.org/W3190774574","https://openalex.org/W3092731089","https://openalex.org/W4287642618","https://openalex.org/W3197035501","https://openalex.org/W2790021258","https://openalex.org/W4232800571","https://openalex.org/W2023409468","https://openalex.org/W2902059015","https://openalex.org/W2981828960"],"abstract_inverted_index":{"The":[0,67,93],"deep":[1],"learning-based":[2],"(DL-based)":[3],"channel":[4],"state":[5],"information":[6],"(CSI)":[7],"feedback":[8,64],"in":[9,75,122],"the":[10,33,37,70,98,102,106],"frequency":[11],"division":[12],"duplexing":[13],"(FDD)":[14],"massive":[15],"multiple-input":[16],"multiple-output":[17],"(MIMO)":[18],"system":[19],"has":[20],"demonstrated":[21],"its":[22],"potential":[23],"and":[24,43,81],"efficiency.":[25],"However,":[26],"conventional":[27],"neural":[28,60,72],"networks":[29,112],"cannot":[30],"fully":[31],"utilize":[32],"complex-valued":[34,58,71],"nature":[35],"of":[36,46,90,105],"downlink":[38],"channel.":[39],"In":[40,52],"addition,":[41],"multi-scale":[42,77],"multi-resolution":[44,83],"features":[45],"CSI":[47,63],"can":[48],"be":[49],"further":[50],"explored.":[51],"this":[53],"letter,":[54],"we":[55],"present":[56],"a":[57,76,82,88,119],"lightweight":[59,91,111],"network":[61,73],"for":[62],"named":[65],"CVLNet.":[66],"CVLNet":[68,100],"adopts":[69],"components":[74],"feature":[78],"augmentation":[79],"encoder":[80,107],"X-shaped":[84],"reconstruction":[85],"decoder":[86],"with":[87,108,116],"series":[89],"details.":[92],"experiment":[94],"results":[95],"show":[96],"that":[97],"proposed":[99],"maintains":[101],"same-level":[103],"parameters":[104],"state-of-the-art":[109],"(SOTA)":[110],"while":[113],"outperforming":[114],"them":[115],"at":[117],"most":[118],"33.4%":[120],"improvement":[121],"accuracy":[123],"under":[124],"severe":[125],"compression":[126],"rates.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}