{"id":"https://openalex.org/W4200613635","doi":"https://doi.org/10.1109/vtc2021-fall52928.2021.9625174","title":"Blind Denoiser-based Beamspace Channel Estimation with GAN in Millimeter- Wave Systems","display_name":"Blind Denoiser-based Beamspace Channel Estimation with GAN in Millimeter- Wave Systems","publication_year":2021,"publication_date":"2021-09-01","ids":{"openalex":"https://openalex.org/W4200613635","doi":"https://doi.org/10.1109/vtc2021-fall52928.2021.9625174"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2021-fall52928.2021.9625174","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2021-fall52928.2021.9625174","pdf_url":null,"source":{"id":"https://openalex.org/S4363607774","display_name":"2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)","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/A5100629241","display_name":"Yinghui Zhang","orcid":"https://orcid.org/0000-0002-6105-0664"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinghui Zhang","raw_affiliation_strings":["College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389531","display_name":"Zhenyu Zhang","orcid":"https://orcid.org/0000-0002-5200-3516"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Zhang","raw_affiliation_strings":["College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100607867","display_name":"Yuxing Zhang","orcid":"https://orcid.org/0000-0002-2541-8687"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxing Zhang","raw_affiliation_strings":["College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102913097","display_name":"Tiankui Zhang","orcid":"https://orcid.org/0000-0002-0694-5844"},"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":"Tiankui Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"01","last_page":"05"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","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"}},"topics":[{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","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/T10752","display_name":"Terahertz technology and applications","score":0.9986000061035156,"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":0.9984999895095825,"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/estimator","display_name":"Estimator","score":0.7302419543266296},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7135659456253052},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6799787878990173},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6359933018684387},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5821289420127869},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5407646894454956},{"id":"https://openalex.org/keywords/extremely-high-frequency","display_name":"Extremely high frequency","score":0.5348137021064758},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5008485317230225},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47840723395347595},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45374566316604614},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4290660619735718},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.42160624265670776},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.4169350564479828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3513278365135193},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.268332839012146},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17190873622894287},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10937342047691345}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7302419543266296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7135659456253052},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6799787878990173},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6359933018684387},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5821289420127869},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5407646894454956},{"id":"https://openalex.org/C45764600","wikidata":"https://www.wikidata.org/wiki/Q570342","display_name":"Extremely high frequency","level":2,"score":0.5348137021064758},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5008485317230225},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47840723395347595},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45374566316604614},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4290660619735718},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.42160624265670776},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.4169350564479828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3513278365135193},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.268332839012146},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17190873622894287},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10937342047691345},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2021-fall52928.2021.9625174","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2021-fall52928.2021.9625174","pdf_url":null,"source":{"id":"https://openalex.org/S4363607774","display_name":"2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8686611579","display_name":"\u6beb\u7c73\u6ce2\u8d85\u5bc6\u96c6\u7f51\u7edc\u4e2d\u9ad8\u80fd\u6548\u7684\u591a\u70b9\u534f\u4f5c\u6ce2\u675f\u8d4b\u578b\u6280\u672f\u7814\u7a76","funder_award_id":"61761033","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2004294022","https://openalex.org/W2098725264","https://openalex.org/W2111953900","https://openalex.org/W2140856955","https://openalex.org/W2195693430","https://openalex.org/W2508457857","https://openalex.org/W2651491514","https://openalex.org/W2724191955","https://openalex.org/W2798278116","https://openalex.org/W2963290405","https://openalex.org/W2963382561","https://openalex.org/W4295521014","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W2978729728","https://openalex.org/W4293226380","https://openalex.org/W4288966080","https://openalex.org/W2545343974","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4291895924","https://openalex.org/W1530347314","https://openalex.org/W4391266461","https://openalex.org/W2590798552"],"abstract_inverted_index":{"The":[0],"number":[1],"of":[2,129],"radio-frequency":[3],"(RF)":[4],"chains":[5],"is":[6,71,151],"limited":[7],"in":[8,73,89],"millimeter-wave":[9,44],"massive":[10,45],"multiple-input":[11],"and":[12,32,53,80,95,111],"multiple-output":[13],"(MIMO)":[14],"systems,":[15],"which":[16,48,150],"brings":[17],"challenges":[18],"to":[19],"channel":[20,51,56,109],"estimation.":[21],"To":[22],"solve":[23],"this":[24,74],"problem,":[25],"we":[26,134],"exploit":[27],"generative":[28],"adversarial":[29],"networks":[30,37,70,84],"(GAN)":[31],"a":[33,40,105,136],"deep":[34],"convolutional":[35],"neural":[36,69],"(CNN)":[38],"for":[39,121],"three-dimensional":[41],"(3D)":[42],"lens":[43],"MIMO":[46],"system,":[47],"could":[49],"learn":[50],"structure":[52],"obtain":[54],"accurate":[55],"estimation":[57,102,110],"from":[58,146,153],"the":[59,78,82,90,143,147,154],"training":[60],"data.":[61],"A":[62],"novel":[63],"GAN-CNN":[64],"blind":[65,138],"denoiser":[66],"(GCBD)":[67],"based":[68],"proposed":[72],"paper.":[75],"Based":[76],"on":[77],"analysis":[79,117],"simulations,":[81],"GCBD":[83],"enjoys":[85],"satisfying":[86],"accuracy":[87],"even":[88],"low":[91],"signal-to-noise":[92],"(SNR)":[93],"region":[94],"significantly":[96],"outperforms":[97],"existing":[98],"algorithms":[99],"with":[100],"lower":[101],"error,":[103],"including":[104],"support":[106],"detection":[107],"(SD)-based":[108],"sparse":[112],"non-informative":[113],"parameter":[114],"estimator-based":[115],"cosparse":[116],"approximate":[118],"message":[119],"passing":[120],"imaging":[122],"(SCAMPI),":[123],"Non-Local":[124],"Means":[125],"(NLM),":[126],"Block":[127],"Method":[128],"3-Dimension":[130],"(BM3D)":[131],"schemes.":[132],"Moreover,":[133],"consider":[135],"typical":[137],"denoising":[139],"problem":[140],"by":[141],"removing":[142],"unknown":[144],"noise":[145],"noisy":[148],"channel,":[149],"different":[152],"exiting":[155],"scheme.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
