{"id":"https://openalex.org/W3160979535","doi":"https://doi.org/10.1109/icassp39728.2021.9414376","title":"Pushing The Limit of Type I Codebook For Fdd Massive Mimo Beamforming: A Channel Covariance Reconstruction Approach","display_name":"Pushing The Limit of Type I Codebook For Fdd Massive Mimo Beamforming: A Channel Covariance Reconstruction Approach","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3160979535","doi":"https://doi.org/10.1109/icassp39728.2021.9414376","mag":"3160979535"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9414376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100399848","display_name":"Kai Li","orcid":"https://orcid.org/0000-0002-0517-2392"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Li","raw_affiliation_strings":["Shenzhen Research Institute of Big Data","The Chinese University of Hong Kong, Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data","institution_ids":["https://openalex.org/I4210099586"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414362","display_name":"Ying Li","orcid":"https://orcid.org/0000-0002-9604-2664"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Li","raw_affiliation_strings":["Shenzhen Research Institute of Big Data","The Chinese University of Hong Kong, Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data","institution_ids":["https://openalex.org/I4210099586"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100625462","display_name":"Lei Cheng","orcid":"https://orcid.org/0000-0002-0097-0547"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Cheng","raw_affiliation_strings":["Shenzhen Research Institute of Big Data"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data","institution_ids":["https://openalex.org/I4210099586"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059252324","display_name":"Qingjiang Shi","orcid":"https://orcid.org/0000-0003-0507-9080"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]},{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingjiang Shi","raw_affiliation_strings":["Shenzhen Research Institute of Big Data","Tongji University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data","institution_ids":["https://openalex.org/I4210099586"]},{"raw_affiliation_string":"Tongji University","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101766226","display_name":"Zhi\u2010Quan Luo","orcid":"https://orcid.org/0000-0003-3995-914X"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi-Quan Luo","raw_affiliation_strings":["Shenzhen Research Institute of Big Data","The Chinese University of Hong Kong, Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data","institution_ids":["https://openalex.org/I4210099586"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.442,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88697242,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4785","last_page":"4789"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9997000098228455,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9997000098228455,"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/T12791","display_name":"Full-Duplex Wireless Communications","score":0.9994999766349792,"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/T10069","display_name":"Antenna Design and Analysis","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/codebook","display_name":"Codebook","score":0.985693097114563},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.8495917320251465},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.6387580037117004},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6274174451828003},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5511408448219299},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.5339098572731018},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5333238840103149},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.5071282386779785},{"id":"https://openalex.org/keywords/precoding","display_name":"Precoding","score":0.48733362555503845},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.46706920862197876},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.43277260661125183},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.38338226079940796},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2579852342605591},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1910429298877716},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.16971364617347717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1695544719696045}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.985693097114563},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.8495917320251465},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.6387580037117004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6274174451828003},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5511408448219299},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.5339098572731018},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5333238840103149},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.5071282386779785},{"id":"https://openalex.org/C160562895","wikidata":"https://www.wikidata.org/wiki/Q7239557","display_name":"Precoding","level":4,"score":0.48733362555503845},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.46706920862197876},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.43277260661125183},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.38338226079940796},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2579852342605591},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1910429298877716},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.16971364617347717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1695544719696045},{"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/icassp39728.2021.9414376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2039538800","https://openalex.org/W2054090890","https://openalex.org/W2064036620","https://openalex.org/W2070426678","https://openalex.org/W2141682101","https://openalex.org/W2576906596","https://openalex.org/W2724724053","https://openalex.org/W2916179838","https://openalex.org/W2938517017","https://openalex.org/W2954359771","https://openalex.org/W2970406288"],"related_works":["https://openalex.org/W2096936443","https://openalex.org/W2081863301","https://openalex.org/W2352648934","https://openalex.org/W2365109233","https://openalex.org/W145510127","https://openalex.org/W2374856816","https://openalex.org/W1977098967","https://openalex.org/W2378932494","https://openalex.org/W2352292447","https://openalex.org/W2391875658"],"abstract_inverted_index":{"There":[0],"is":[1,117],"a":[2],"fundamental":[3],"trade-off":[4],"between":[5,155],"the":[6,13,19,57,83,91,110,141,145,153,179,183],"channel":[7,68,166,172],"representation":[8],"resolution":[9,53],"of":[10,15,40,182,188],"codebooks":[11,41],"and":[12,32,45,54,73],"overheads":[14],"feedback":[16,65],"communications":[17],"in":[18,101,125,135,149,186],"fifth":[20],"generation":[21],"new":[22],"radio":[23],"(5G":[24],"NR)":[25],"frequency":[26],"division":[27],"duplex":[28],"(FDD)":[29],"massive":[30],"multiple-input":[31],"multiple-output":[33],"(MIMO)":[34],"systems.":[35],"In":[36],"particular,":[37],"two":[38,157],"types":[39],"(namely":[42],"Type":[43,46,58,84,92,111,129],"I":[44,59,93,130],"II":[47,85,112],"codebooks)":[48],"are":[49,76,175],"introduced":[50],"with":[51],"different":[52],"overhead.":[55],"Although":[56],"codebook":[60,86,94,113,158],"based":[61,87,95,114,159,164],"scheme":[62,96,115],"requires":[63],"lower":[64],"overhead,":[66],"its":[67],"state":[69],"information":[70],"(CSI)":[71],"reconstruction":[72,143],"beamforming":[74,160,189],"performance":[75,181],"not":[77],"as":[78,80],"good":[79],"those":[81],"from":[82,168],"scheme.":[88],"However,":[89],"since":[90],"has":[97],"been":[98],"widely":[99],"used":[100],"4G":[102],"systems":[103],"for":[104],"many":[105],"years,":[106],"replacing":[107],"it":[108],"by":[109],"overnight":[116],"too":[118],"costly":[119],"to":[120,139,151,177],"be":[121],"an":[122],"option.":[123],"Therefore,":[124],"this":[126],"paper,":[127],"using":[128],"codebook,":[131],"we":[132],"leverage":[133],"advances":[134],"cutting":[136],"plane":[137],"method":[138],"optimize":[140],"CSI":[142],"at":[144],"base":[146],"station":[147],"(BS),":[148],"order":[150],"close":[152],"gap":[154],"these":[156],"schemes.":[161],"Numerical":[162],"results":[163],"on":[165],"samples":[167],"QUAsi":[169],"Deterministic":[170],"RadIo":[171],"GenerAtor":[173],"(QuaDRiGa)":[174],"presented":[176],"show":[178],"excellent":[180],"proposed":[184],"algorithm":[185],"terms":[187],"vector":[190],"acquisition.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}