{"id":"https://openalex.org/W4312987286","doi":"https://doi.org/10.1109/tsp.2022.3220036","title":"Comments on \u201cSpatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO\u201d","display_name":"Comments on \u201cSpatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO\u201d","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312987286","doi":"https://doi.org/10.1109/tsp.2022.3220036"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2022.3220036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3220036","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","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/A5067236454","display_name":"Jinsub Kim","orcid":"https://orcid.org/0000-0002-0119-8632"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jinsub Kim","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, USA","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079003845","display_name":"Sharmin Kibria","orcid":"https://orcid.org/0000-0002-5726-1100"},"institutions":[{"id":"https://openalex.org/I887054487","display_name":"MathWorks (United States)","ror":"https://ror.org/01n8qtk87","country_code":"US","type":"company","lineage":["https://openalex.org/I887054487"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sharmin Kibria","raw_affiliation_strings":["Mathworks, Natick, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mathworks, Natick, MA, USA","institution_ids":["https://openalex.org/I887054487"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067236454"],"corresponding_institution_ids":["https://openalex.org/I131249849"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15525939,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"70","issue":null,"first_page":"5349","last_page":"5350"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/identifiability","display_name":"Identifiability","score":0.9403676390647888},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6938599944114685},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5923334360122681},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5917707085609436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5604878067970276},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5312286019325256},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.51372230052948},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4983489513397217},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4659833312034607},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4511992335319519},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38065284490585327},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09652894735336304},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.07318621873855591}],"concepts":[{"id":"https://openalex.org/C122770356","wikidata":"https://www.wikidata.org/wiki/Q1656753","display_name":"Identifiability","level":2,"score":0.9403676390647888},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6938599944114685},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5923334360122681},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5917707085609436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5604878067970276},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5312286019325256},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.51372230052948},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4983489513397217},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4659833312034607},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4511992335319519},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38065284490585327},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09652894735336304},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.07318621873855591},{"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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2022.3220036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3220036","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1770500012","https://openalex.org/W1938636034","https://openalex.org/W2164696938","https://openalex.org/W2790127798","https://openalex.org/W2919760977","https://openalex.org/W2963805188","https://openalex.org/W4300263211"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2156466545","https://openalex.org/W2379468505","https://openalex.org/W3104324607","https://openalex.org/W4206981968","https://openalex.org/W1987102304","https://openalex.org/W4285251805","https://openalex.org/W2537887767","https://openalex.org/W1606356673","https://openalex.org/W2601968125"],"abstract_inverted_index":{"In":[0,140,158],"the":[1,13,39,44,66,76,82,103,113,122,137,155,164],"generalized":[2],"multiple":[3,18],"measurement":[4,84],"vectors":[5,21,51,74,111,127,178],"(GMMV)":[6],"setup":[7,41,68,87,124,166],"of":[8,15,31,38,47,71,92,108],"compressive":[9],"sensing,":[10],"we":[11,89,143],"consider":[12],"problem":[14],"jointly":[16],"recovering":[17],"sparse":[19,49,72,94,109,151],"signal":[20,50,73,95,110,126,152,177],"sharing":[22],"a":[23,147],"common":[24],"sparsity":[25],"pattern":[26],"based":[27],"on":[28,106,150],"joint":[29],"analysis":[30],"their":[32,181],"linear":[33,45],"measurements.":[34],"The":[35],"important":[36],"aspect":[37],"GMMV":[40,67,114,123,156,165],"is":[42,60,119,161],"that":[43,121,163],"measurements":[46],"different":[48,56],"are":[52,183],"acquired":[53],"by":[54],"using":[55],"sensing":[57],"matrices.":[58],"It":[59],"not":[61,168],"yet":[62],"well":[63],"understood":[64],"how":[65],"affects":[69],"identifiability":[70,107,153,173],"from":[75],"measurements,":[77],"in":[78,112,116,154,170],"particular":[79],"compared":[80,135],"to":[81,132,136,145],"single":[83],"vector":[85,96],"(SMV)":[86],"wherein":[88],"perform":[90],"recovery":[91],"each":[93],"independently.":[97],"Gao":[98],"et":[99],"al.":[100],"[1]":[101],"presented":[102],"first":[104],"theorem":[105],"setup,":[115],"which":[117],"it":[118,160],"stated":[120],"allows":[125],"with":[128],"more":[129],"nonzero":[130],"rows":[131],"be":[133],"identifiable":[134],"SMV":[138],"setup.":[139,157],"this":[141],"correspondence,":[142],"aim":[144],"present":[146],"contrasting":[148],"perspective":[149],"particular,":[159],"shown":[162],"does":[167],"result":[169],"an":[171],"improved":[172],"condition":[174],"for":[175],"some":[176],"even":[179],"when":[180],"entries":[182],"diverse.":[184]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}