{"id":"https://openalex.org/W7147296809","doi":"https://doi.org/10.1109/lwc.2026.3679737","title":"Robust Adaptive Beamforming via Block Sparse Bayesian Learning and Covariance Matrix Reconstruction in the Presence of Gain-Phase Errors","display_name":"Robust Adaptive Beamforming via Block Sparse Bayesian Learning and Covariance Matrix Reconstruction in the Presence of Gain-Phase Errors","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7147296809","doi":"https://doi.org/10.1109/lwc.2026.3679737"},"language":null,"primary_location":{"id":"doi:10.1109/lwc.2026.3679737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2026.3679737","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"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 Wireless Communications Letters","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":null,"display_name":"Xuanrui Zhang","orcid":"https://orcid.org/0009-0001-4536-9421"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanrui Zhang","raw_affiliation_strings":["School of Electronics and Information and the National Key Laboratory of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0009-0001-4536-9421","affiliations":[{"raw_affiliation_string":"School of Electronics and Information and the National Key Laboratory of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044105692","display_name":"Yuexian Wang","orcid":"https://orcid.org/0000-0002-3622-6162"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuexian Wang","raw_affiliation_strings":["School of Electronics and Information and the National Key Laboratory of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-3622-6162","affiliations":[{"raw_affiliation_string":"School of Electronics and Information and the National Key Laboratory of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132555491","display_name":"Chuang Han","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuang Han","raw_affiliation_strings":["School of Electronics and Information and the National Key Laboratory of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information and the National Key Laboratory of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132617117","display_name":"Ling Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Wang","raw_affiliation_strings":["School of Electronics and Information and the National Key Laboratory of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-6678-7198","affiliations":[{"raw_affiliation_string":"School of Electronics and Information and the National Key Laboratory of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114219786","display_name":"C. Tellambura","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chintha Tellambura","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0002-9419-7195","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056145687","display_name":"M\u00e9rouane Debbah","orcid":"https://orcid.org/0000-0001-8941-8080"},"institutions":[{"id":"https://openalex.org/I176601375","display_name":"Khalifa University of Science and Technology","ror":"https://ror.org/05hffr360","country_code":"AE","type":"education","lineage":["https://openalex.org/I176601375"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"M\u00e9rouane Debbah","raw_affiliation_strings":["Research Institute for Digital Future, Khalifa University, Abu Dhabi, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0001-8941-8080","affiliations":[{"raw_affiliation_string":"Research Institute for Digital Future, Khalifa University, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I176601375"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33478261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":null,"first_page":"2433","last_page":"2437"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.8751000165939331,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.8751000165939331,"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/T10860","display_name":"Speech and Audio Processing","score":0.05959999933838844,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.012000000104308128,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/robustness","display_name":"Robustness (evolution)","score":0.6693000197410583},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.629800021648407},{"id":"https://openalex.org/keywords/adaptive-beamformer","display_name":"Adaptive beamformer","score":0.5892000198364258},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.5016000270843506},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4941999912261963},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.490200012922287},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.48339998722076416}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6693000197410583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6414999961853027},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.629800021648407},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6044999957084656},{"id":"https://openalex.org/C33378366","wikidata":"https://www.wikidata.org/wiki/Q4680719","display_name":"Adaptive beamformer","level":3,"score":0.5892000198364258},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.5016000270843506},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4941999912261963},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.490200012922287},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.48339998722076416},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4471000134944916},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.42910000681877136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3465000092983246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30480000376701355},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.3018999993801117},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2946000099182129},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lwc.2026.3679737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2026.3679737","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"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 Wireless Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G623740398","display_name":null,"funder_award_id":"62571436","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8717586252","display_name":null,"funder_award_id":"62571452","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"letter":[1],"addresses":[2],"the":[3,53,59,65,96,102,123],"problem":[4],"of":[5,143],"robust":[6,110],"adaptive":[7,111],"beamforming":[8],"for":[9,40,115],"linear":[10],"arrays":[11],"impaired":[12],"by":[13],"gain-phase":[14,35,57,135],"errors.":[15],"We":[16],"propose":[17],"a":[18,46,70,108],"joint":[19],"calibration":[20],"and":[21,37,130],"estimation":[22],"method":[23],"based":[24],"on":[25,101],"block":[26],"sparse":[27],"Bayesian":[28,48],"learning,":[29],"in":[30,69,151],"which":[31],"all":[32],"unknown":[33],"parameters\u2014including":[34],"errors":[36],"those":[38],"required":[39],"covariance":[41,98],"matrix":[42],"reconstruction\u2014are":[43],"incorporated":[44],"into":[45],"unified":[47],"inference":[49],"framework.":[50],"By":[51],"reparameterizing":[52],"steering":[54],"vector":[55],"with":[56],"perturbations,":[58],"error":[60,136],"structure":[61],"is":[62,82,113],"decoupled":[63],"from":[64],"overcomplete":[66],"dictionary,":[67],"resulting":[68],"fully":[71],"deterministic":[72],"dictionary":[73],"that":[74,122],"requires":[75],"no":[76],"further":[77],"learning.":[78],"An":[79],"expectation\u2013maximization":[80],"procedure":[81],"employed":[83],"to":[84,94,145],"iteratively":[85],"estimate":[86],"these":[87],"parameters.":[88],"The":[89],"estimates":[90],"are":[91],"then":[92],"used":[93],"reconstruct":[95],"interference-plus-noise":[97],"matrix.":[99],"Based":[100],"minimum":[103],"variance":[104],"distortionless":[105],"response":[106],"principle,":[107],"novel":[109],"beamformer":[112,125],"developed":[114],"partially":[116],"calibrated":[117],"arrays.":[118],"Simulation":[119],"results":[120],"demonstrate":[121],"proposed":[124],"significantly":[126],"enhances":[127],"output":[128,140],"performance":[129],"exhibits":[131],"strong":[132],"robustness":[133],"under":[134],"mismatches,":[137],"achieving":[138],"an":[139],"SINR":[141],"improvement":[142],"up":[144],"3":[146],"dB":[147],"over":[148],"state-of-the-art":[149],"methods":[150],"low":[152],"SNR":[153],"scenarios.":[154]},"counts_by_year":[],"updated_date":"2026-04-08T06:01:36.053099","created_date":"2026-04-02T00:00:00"}