{"id":"https://openalex.org/W3036876996","doi":"https://doi.org/10.1109/wcnc45663.2020.9120807","title":"Deep Learning based Low-Rank Channel Recovery for Hybrid Beamforming in Millimeter-Wave Massive MIMO","display_name":"Deep Learning based Low-Rank Channel Recovery for Hybrid Beamforming in Millimeter-Wave Massive MIMO","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3036876996","doi":"https://doi.org/10.1109/wcnc45663.2020.9120807","mag":"3036876996"},"language":"en","primary_location":{"id":"doi:10.1109/wcnc45663.2020.9120807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcnc45663.2020.9120807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","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/A5110228073","display_name":"Nuan Song","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099903","display_name":"Nokia (China)","ror":"https://ror.org/01607kg94","country_code":"CN","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210099903"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nuan Song","raw_affiliation_strings":["Nokia Bell Labs, China"],"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, China","institution_ids":["https://openalex.org/I4210099903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066009762","display_name":"Chenhui Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099903","display_name":"Nokia (China)","ror":"https://ror.org/01607kg94","country_code":"CN","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210099903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenhui Ye","raw_affiliation_strings":["Nokia Bell Labs, China"],"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, China","institution_ids":["https://openalex.org/I4210099903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050750924","display_name":"Xiao Hu","orcid":"https://orcid.org/0000-0003-1128-4099"},"institutions":[{"id":"https://openalex.org/I4210099903","display_name":"Nokia (China)","ror":"https://ror.org/01607kg94","country_code":"CN","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210099903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofeng Hu","raw_affiliation_strings":["Nokia Bell Labs, China"],"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, China","institution_ids":["https://openalex.org/I4210099903"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053207353","display_name":"Tao Yang","orcid":"https://orcid.org/0000-0002-9870-6866"},"institutions":[{"id":"https://openalex.org/I4210099903","display_name":"Nokia (China)","ror":"https://ror.org/01607kg94","country_code":"CN","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210099903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Yang","raw_affiliation_strings":["Nokia Bell Labs, China"],"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, China","institution_ids":["https://openalex.org/I4210099903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110228073"],"corresponding_institution_ids":["https://openalex.org/I4210099903"],"apc_list":null,"apc_paid":null,"fwci":0.3082,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.56027357,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":1.0,"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":1.0,"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/T10262","display_name":"Microwave Engineering and Waveguides","score":0.9995999932289124,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9991000294685364,"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/mimo","display_name":"MIMO","score":0.8243616819381714},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.6943583488464355},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.690737783908844},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6576485633850098},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.6461696028709412},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49276188015937805},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.49140870571136475},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.47718632221221924},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47440052032470703},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4514169692993164},{"id":"https://openalex.org/keywords/3g-mimo","display_name":"3G MIMO","score":0.44865673780441284},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44549939036369324},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.43310344219207764},{"id":"https://openalex.org/keywords/extremely-high-frequency","display_name":"Extremely high frequency","score":0.43111562728881836},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4294971525669098},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.423606812953949},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42265403270721436},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39523857831954956},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19207513332366943},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18550068140029907},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.18014919757843018},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.15971696376800537}],"concepts":[{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.8243616819381714},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.6943583488464355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.690737783908844},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6576485633850098},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.6461696028709412},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49276188015937805},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.49140870571136475},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.47718632221221924},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47440052032470703},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4514169692993164},{"id":"https://openalex.org/C165650700","wikidata":"https://www.wikidata.org/wiki/Q4636347","display_name":"3G MIMO","level":4,"score":0.44865673780441284},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44549939036369324},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.43310344219207764},{"id":"https://openalex.org/C45764600","wikidata":"https://www.wikidata.org/wiki/Q570342","display_name":"Extremely high frequency","level":2,"score":0.43111562728881836},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4294971525669098},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.423606812953949},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42265403270721436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39523857831954956},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19207513332366943},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18550068140029907},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.18014919757843018},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.15971696376800537},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/wcnc45663.2020.9120807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcnc45663.2020.9120807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","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":25,"referenced_works":["https://openalex.org/W2053521124","https://openalex.org/W2075148031","https://openalex.org/W2088212435","https://openalex.org/W2111953900","https://openalex.org/W2127271355","https://openalex.org/W2137628444","https://openalex.org/W2167956149","https://openalex.org/W2195693430","https://openalex.org/W2339667469","https://openalex.org/W2548842562","https://openalex.org/W2559695533","https://openalex.org/W2615358882","https://openalex.org/W2738594702","https://openalex.org/W2782878075","https://openalex.org/W2798574788","https://openalex.org/W2888966884","https://openalex.org/W2937643630","https://openalex.org/W2952350176","https://openalex.org/W2962785465","https://openalex.org/W2962895431","https://openalex.org/W2963290405","https://openalex.org/W2963408914","https://openalex.org/W4297824792","https://openalex.org/W6744033374","https://openalex.org/W6999787859"],"related_works":["https://openalex.org/W2963170046","https://openalex.org/W2088352174","https://openalex.org/W3084132786","https://openalex.org/W4327661444","https://openalex.org/W2034991012","https://openalex.org/W2724724053","https://openalex.org/W4380894509","https://openalex.org/W2982570613","https://openalex.org/W2804205664","https://openalex.org/W4285223123"],"abstract_inverted_index":{"Massive":[0],"Multiple":[1,3],"Input":[2],"Output":[4],"(MIMO)":[5],"at":[6],"millimeter":[7,179],"wave":[8,180],"bands":[9],"is":[10,29,45],"able":[11],"to":[12,139,157],"boost":[13],"the":[14,21,30,33,39,51,103,112,123,127,136,140,171],"system":[15],"throughput.":[16],"A":[17],"key":[18,132],"challenge":[19],"for":[20,83],"hybrid":[22,85],"beamforming":[23],"design":[24],"in":[25,178],"massive":[26,88,181],"MIMO":[27,89,182],"systems":[28],"acquisition":[31],"of":[32,41,50,173],"full":[34,141],"channel":[35,80,142],"state":[36],"information,":[37],"since":[38],"number":[40],"radio":[42],"frequency":[43],"chains":[44],"much":[46],"smaller":[47],"than":[48],"that":[49],"antennas.":[52],"Conventional":[53],"methods":[54],"require":[55],"a":[56,60,84,97],"longer":[57],"measurement":[58],"time,":[59],"large":[61],"overhead,":[62],"or":[63],"costly":[64],"signal":[65],"processing":[66],"efforts.":[67],"Therefore,":[68],"we":[69],"propose":[70],"an":[71,148],"efficient":[72,149],"and":[73,102,152,165],"adaptable":[74,104,131],"deep":[75,175],"neural":[76,93,114],"network":[77,94,115],"based":[78,87],"low-rank":[79,128],"recovery":[81,105,133],"scheme":[82],"array":[86],"system.":[90],"The":[91,107,130,144],"proposed":[92,145],"architecture":[95,146],"includes":[96],"common":[98],"feature":[99,108],"extraction":[100],"module":[101,134],"module.":[106],"extraction,":[109],"built":[110],"on":[111],"convolutional":[113],"with":[116,167],"residual":[117],"learning":[118,150,176],"functionality,":[119],"can":[120,153],"efficiently":[121],"learn":[122],"essential":[124,137],"features":[125,138],"from":[126],"measurements.":[129],"maps":[135],"information.":[143],"enables":[147],"procedure":[151],"be":[154],"easily":[155],"adapted":[156],"different":[158],"cases.":[159],"Simulation":[160],"results":[161],"are":[162],"carried":[163],"out":[164],"compared":[166],"existing":[168],"solutions,":[169],"showing":[170],"potential":[172],"applying":[174],"concepts":[177],"systems.":[183]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
