{"id":"https://openalex.org/W4399801014","doi":"https://doi.org/10.1109/tsp.2024.3416543","title":"Bayesian Algorithms for Kronecker-Structured Sparse Vector Recovery With Application to IRS-MIMO Channel Estimation","display_name":"Bayesian Algorithms for Kronecker-Structured Sparse Vector Recovery With Application to IRS-MIMO Channel Estimation","publication_year":2024,"publication_date":"2024-06-19","ids":{"openalex":"https://openalex.org/W4399801014","doi":"https://doi.org/10.1109/tsp.2024.3416543"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2024.3416543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3416543","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/A5074750235","display_name":"Yanbin He","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Yanbin He","raw_affiliation_strings":["Signal Processing Systems Group, Electrical Engineering, Mathematics, and Computer Science Faculty, Delft University of Technology, Delft, CD, The Netherlands","Signal Processing Systems group, Electrical Engineering, Mathematics, Computer Science faculty, Delft University of Technology, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Signal Processing Systems Group, Electrical Engineering, Mathematics, and Computer Science Faculty, Delft University of Technology, Delft, CD, The Netherlands","institution_ids":["https://openalex.org/I98358874"]},{"raw_affiliation_string":"Signal Processing Systems group, Electrical Engineering, Mathematics, Computer Science faculty, Delft University of Technology, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012419698","display_name":"Geethu Joseph","orcid":"https://orcid.org/0000-0002-5289-5403"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Geethu Joseph","raw_affiliation_strings":["Signal Processing Systems Group, Electrical Engineering, Mathematics, and Computer Science Faculty, Delft University of Technology, Delft, CD, The Netherlands","Signal Processing Systems group, Electrical Engineering, Mathematics, Computer Science faculty, Delft University of Technology, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Signal Processing Systems Group, Electrical Engineering, Mathematics, and Computer Science Faculty, Delft University of Technology, Delft, CD, The Netherlands","institution_ids":["https://openalex.org/I98358874"]},{"raw_affiliation_string":"Signal Processing Systems group, Electrical Engineering, Mathematics, Computer Science faculty, Delft University of Technology, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074750235"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":2.2502,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88467716,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"73","issue":null,"first_page":"142","last_page":"157"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9825999736785889,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9825999736785889,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9771000146865845,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9639999866485596,"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/kronecker-delta","display_name":"Kronecker delta","score":0.7465353012084961},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6596987247467041},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5888770818710327},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5850691795349121},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5327237844467163},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5016844272613525},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4218288064002991},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34324586391448975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30654004216194153},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1834515929222107}],"concepts":[{"id":"https://openalex.org/C39482219","wikidata":"https://www.wikidata.org/wiki/Q192826","display_name":"Kronecker delta","level":2,"score":0.7465353012084961},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6596987247467041},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5888770818710327},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5850691795349121},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5327237844467163},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5016844272613525},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4218288064002991},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34324586391448975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30654004216194153},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1834515929222107},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2024.3416543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3416543","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1593447321","https://openalex.org/W1765998458","https://openalex.org/W1940321820","https://openalex.org/W1964921104","https://openalex.org/W2001380973","https://openalex.org/W2033419225","https://openalex.org/W2049502219","https://openalex.org/W2053742104","https://openalex.org/W2066792693","https://openalex.org/W2070669938","https://openalex.org/W2071282831","https://openalex.org/W2119237435","https://openalex.org/W2148154358","https://openalex.org/W2151932824","https://openalex.org/W2151948222","https://openalex.org/W2490662969","https://openalex.org/W2787894218","https://openalex.org/W2790212948","https://openalex.org/W2904975109","https://openalex.org/W2933910221","https://openalex.org/W2979442703","https://openalex.org/W2985466239","https://openalex.org/W2991532537","https://openalex.org/W3122441743","https://openalex.org/W3129036490","https://openalex.org/W3155357069","https://openalex.org/W3165210976","https://openalex.org/W3198279229","https://openalex.org/W3203882385","https://openalex.org/W3204184545","https://openalex.org/W4210751617","https://openalex.org/W4252814261","https://openalex.org/W4285114445","https://openalex.org/W4285120591","https://openalex.org/W4287887619","https://openalex.org/W4289792593","https://openalex.org/W4291236916","https://openalex.org/W4372346791","https://openalex.org/W4383460730","https://openalex.org/W6635971341","https://openalex.org/W6757404076"],"related_works":["https://openalex.org/W3153509215","https://openalex.org/W4301793409","https://openalex.org/W1986375199","https://openalex.org/W300594107","https://openalex.org/W1178061417","https://openalex.org/W2028667466","https://openalex.org/W2030956755","https://openalex.org/W2789582299","https://openalex.org/W3033877930","https://openalex.org/W2323318744"],"abstract_inverted_index":{"We":[0,21,122,152],"study":[1,154],"the":[2,26,35,46,72,93,98,102,129,142,150,155,161,164,175,179,185,193,200],"sparse":[3,19,27,170],"recovery":[4],"problem":[5,24,68],"with":[6,49],"an":[7,134],"underdetermined":[8],"linear":[9],"system":[10,139],"characterized":[11],"by":[12,56],"a":[13,17,39,50,57,62,78],"Kronecker-structured":[14,47,58],"dictionary":[15],"and":[16,32,77,120,140,172],"Kronecker-supported":[18],"vector.":[20],"cast":[22],"this":[23,42],"into":[25],"Bayesian":[28],"learning":[29],"(SBL)":[30],"framework":[31],"rely":[33],"on":[34],"expectation-maximization":[36],"method":[37,76,95],"for":[38],"solution.":[40],"To":[41],"end,":[43],"we":[44,89],"model":[45],"support":[48],"hierarchical":[51],"Gaussian":[52],"prior":[53],"distribution":[54],"parameterized":[55],"hyperparameter,":[59],"leading":[60],"to":[61,97,116,127,145,158,199],"non-convex":[63],"optimization":[64,67],"problem.":[65],"The":[66,106],"is":[69,113],"solved":[70],"using":[71],"alternating":[73],"minimization":[74],"(AM)":[75],"singular":[79],"value":[80],"decomposition":[81],"(SVD)-based":[82],"method,":[83,108],"resulting":[84],"in":[85,133,149],"two":[86],"algorithms.":[87],"Further,":[88],"analytically":[90],"guarantee":[91],"that":[92,160,173],"AM-based":[94,143],"converges":[96],"stationary":[99],"point":[100],"of":[101,163,181,184,195],"SBL":[103,156,186],"cost":[104,157,165,187],"function.":[105,188],"SVD-based":[107],"though":[109],"it":[110],"adopts":[111],"approximations,":[112],"empirically":[114],"shown":[115],"be":[117],"more":[118],"efficient":[119],"accurate.":[121],"then":[123],"apply":[124],"our":[125,196],"algorithm":[126,144],"estimate":[128],"uplink":[130],"wireless":[131],"channel":[132],"intelligent":[135],"reflecting":[136],"surface-aided":[137],"MIMO":[138],"extend":[141],"address":[146],"block":[147],"sparsity":[148],"channel.":[151],"also":[153],"show":[159],"minima":[162,183],"function":[166],"are":[167],"achieved":[168],"at":[169],"solutions":[171],"incorporating":[174],"Kronecker":[176],"structure":[177],"reduces":[178],"number":[180],"local":[182],"Our":[189],"numerical":[190],"results":[191],"demonstrate":[192],"effectiveness":[194],"algorithms":[197],"compared":[198],"state-of-the-art.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}