{"id":"https://openalex.org/W4382999241","doi":"https://doi.org/10.1109/tvt.2023.3291693","title":"Model-Driven Deep Learning-Based Sparse Channel Representation and Recovery for Wideband mmWave Massive MIMO Systems","display_name":"Model-Driven Deep Learning-Based Sparse Channel Representation and Recovery for Wideband mmWave Massive MIMO Systems","publication_year":2023,"publication_date":"2023-07-03","ids":{"openalex":"https://openalex.org/W4382999241","doi":"https://doi.org/10.1109/tvt.2023.3291693"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2023.3291693","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3291693","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Transactions on Vehicular Technology","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/A5101438226","display_name":"Jianqiao Chen","orcid":"https://orcid.org/0000-0003-3491-9237"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqiao Chen","raw_affiliation_strings":["Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-3491-9237","affiliations":[{"raw_affiliation_string":"Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038040039","display_name":"Fanyang Meng","orcid":"https://orcid.org/0000-0001-5725-2178"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanyang Meng","raw_affiliation_strings":["Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-5725-2178","affiliations":[{"raw_affiliation_string":"Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008846998","display_name":"Nan Ma","orcid":"https://orcid.org/0000-0002-2302-7148"},"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"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Ma","raw_affiliation_strings":["Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China","State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2302-7148","affiliations":[{"raw_affiliation_string":"Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061030501","display_name":"Xiaodong Xu","orcid":"https://orcid.org/0000-0003-4245-5989"},"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"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Xu","raw_affiliation_strings":["Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China","State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4245-5989","affiliations":[{"raw_affiliation_string":"Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100405787","display_name":"Ping Zhang","orcid":"https://orcid.org/0000-0002-0269-104X"},"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"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Zhang","raw_affiliation_strings":["Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China","State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0269-104X","affiliations":[{"raw_affiliation_string":"Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, 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":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3499,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.80618057,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"72","issue":"12","first_page":"16788","last_page":"16793"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9747999906539917,"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":0.9652000069618225,"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":0.634484052658081},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5874365568161011},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.558706521987915},{"id":"https://openalex.org/keywords/wideband","display_name":"Wideband","score":0.5576942563056946},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.48068031668663025},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4632861018180847},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4467580020427704},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4430628716945648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43715721368789673},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4234824776649475},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41683024168014526},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.35201817750930786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20760399103164673},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.19628161191940308},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14950942993164062},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10236263275146484},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10205888748168945}],"concepts":[{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.634484052658081},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5874365568161011},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.558706521987915},{"id":"https://openalex.org/C2780202535","wikidata":"https://www.wikidata.org/wiki/Q4524457","display_name":"Wideband","level":2,"score":0.5576942563056946},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.48068031668663025},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4632861018180847},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4467580020427704},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4430628716945648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43715721368789673},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4234824776649475},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41683024168014526},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.35201817750930786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20760399103164673},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.19628161191940308},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14950942993164062},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10236263275146484},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10205888748168945},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2023.3291693","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3291693","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Transactions on Vehicular Technology","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":21,"referenced_works":["https://openalex.org/W143004564","https://openalex.org/W2000721204","https://openalex.org/W2508393166","https://openalex.org/W2553591559","https://openalex.org/W2576906596","https://openalex.org/W2578797046","https://openalex.org/W2596873572","https://openalex.org/W2605368703","https://openalex.org/W2619204584","https://openalex.org/W2768388424","https://openalex.org/W2933010605","https://openalex.org/W2945858715","https://openalex.org/W2963206527","https://openalex.org/W2980231147","https://openalex.org/W2989714518","https://openalex.org/W3081258430","https://openalex.org/W3091391704","https://openalex.org/W3091752016","https://openalex.org/W3167779900","https://openalex.org/W4226057760","https://openalex.org/W4226124428"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W4300044672","https://openalex.org/W2810730439","https://openalex.org/W1881631164","https://openalex.org/W3112081258","https://openalex.org/W2358292267","https://openalex.org/W4200358983","https://openalex.org/W1483997978","https://openalex.org/W2611619770"],"abstract_inverted_index":{"In":[0],"this":[1,79],"paper,":[2],"we":[3,39,102],"exploit":[4],"a":[5,90,125,140],"novel":[6],"model-driven":[7],"deep":[8],"learning":[9,108],"(MDDL)-based":[10],"scheme":[11,160],"for":[12,27,69,115],"efficient":[13],"wideband":[14],"millimeter-wave":[15],"(mmWave)":[16],"massive":[17],"multiple-input":[18],"multiple-output":[19],"(MIMO)":[20],"channel":[21,29,71,117,158],"estimation":[22,159],"where":[23,143],"the":[24,37,48,55,81,100,120,152,155],"neural":[25,82],"networks":[26],"sparse":[28,70,116],"representation":[30,72],"and":[31,165],"recovery":[32],"are":[33,147],"respectively":[34],"designed.":[35],"For":[36,99],"former,":[38],"propose":[40,103],"an":[41,66,104],"<italic":[42,111],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[43,112],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">angular-resampling":[44],"network</i>":[45,114],"to":[46,54],"determine":[47],"sampling":[49],"intervals":[50],"of":[51,58,61,85,154],"grids":[52],"adaptive":[53],"true":[56],"angles":[57],"arrival":[59],"(AoAs)":[60],"paths,":[62],"based":[63],"on":[64],"which":[65,135],"effective":[67],"dictionary":[68],"in":[73],"angle-domain":[74],"can":[75],"be":[76],"constructed.":[77],"To":[78],"end,":[80],"network":[83],"consisting":[84],"three":[86],"modules":[87],"trained":[88],"with":[89,161],"newly-designed":[91],"angular":[92],"Gaussian-mixture":[93],"distribution":[94],"loss":[95],"function":[96],"is":[97,132,136],"developed.":[98],"latter,":[101],"inverse-free":[105],"variational":[106],"Bayesian":[107],"(IF-VBL)":[109],"driven":[110],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">deep-unfolding":[113],"recovery.":[118],"Specifically,":[119],"IF-VBL":[121],"method":[122],"by":[123],"maximizing":[124],"general":[126],"relaxed":[127],"evidence":[128],"lower":[129],"bound":[130],"(ELBO)":[131],"first":[133],"developed,":[134],"then":[137],"unfolded":[138],"into":[139],"layer-wise":[141],"architecture":[142],"some":[144],"a-priori":[145],"parameters":[146],"learned.":[148],"Simulation":[149],"results":[150],"verify":[151],"superiority":[153],"proposed":[156],"MDDL-based":[157],"significantly":[162],"improved":[163],"convergence":[164],"performance":[166],"over":[167],"counterparts.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
