{"id":"https://openalex.org/W4414538903","doi":"https://doi.org/10.1109/icc52391.2025.11162031","title":"XL-MIMO Near-Field Localization with Bayesian Message Passing","display_name":"XL-MIMO Near-Field Localization with Bayesian Message Passing","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414538903","doi":"https://doi.org/10.1109/icc52391.2025.11162031"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11162031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11162031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5052048704","display_name":"Mingfeng Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingfeng Cheng","raw_affiliation_strings":["Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400573","display_name":"Li Nian","orcid":"https://orcid.org/0000-0001-8538-1137"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nian Li","raw_affiliation_strings":["Northest Forestry University,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northest Forestry University,Harbin,China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079717222","display_name":"Lu Meng","orcid":"https://orcid.org/0000-0003-4078-8480"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Lu","raw_affiliation_strings":["Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056985483","display_name":"H. Peng","orcid":"https://orcid.org/0009-0003-2780-0331"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojin Peng","raw_affiliation_strings":["Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055023503","display_name":"Wei Peng","orcid":"https://orcid.org/0000-0002-9087-9551"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Peng","raw_affiliation_strings":["Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]}],"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":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"06"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998999834060669,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998999834060669,"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/T11946","display_name":"Antenna Design and Optimization","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9990000128746033,"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/computational-complexity-theory","display_name":"Computational complexity theory","score":0.6611999869346619},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.6482999920845032},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.49160000681877136},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.46399998664855957},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.43880000710487366},{"id":"https://openalex.org/keywords/eigendecomposition-of-a-matrix","display_name":"Eigendecomposition of a matrix","score":0.41659998893737793},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.3804999887943268},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.37290000915527344},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.37119999527931213}],"concepts":[{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.6611999869346619},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.6482999920845032},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6362000107765198},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.552299976348877},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.49160000681877136},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.46399998664855957},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.43880000710487366},{"id":"https://openalex.org/C169756996","wikidata":"https://www.wikidata.org/wiki/Q194919","display_name":"Eigendecomposition of a matrix","level":3,"score":0.41659998893737793},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36800000071525574},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36059999465942383},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.3310999870300293},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C62191587","wikidata":"https://www.wikidata.org/wiki/Q4771249","display_name":"Antenna array","level":3,"score":0.31769999861717224},{"id":"https://openalex.org/C39425265","wikidata":"https://www.wikidata.org/wiki/Q7098944","display_name":"Optimal estimation","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11162031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11162031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6770860154","display_name":null,"funder_award_id":"62171192","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2019945856","https://openalex.org/W2513373031","https://openalex.org/W2803130179","https://openalex.org/W2914090143","https://openalex.org/W2963206527","https://openalex.org/W3047915604","https://openalex.org/W3126700919","https://openalex.org/W3194646605","https://openalex.org/W3203882385","https://openalex.org/W4297094903","https://openalex.org/W4364322798"],"related_works":[],"abstract_inverted_index":{"Extra-large":[0],"scale":[1],"massive":[2],"multiple-input":[3],"multipleoutput":[4],"(XL-MIMO)":[5],"significantly":[6],"enhances":[7],"the":[8,15,26,43,51,68,72,86,100,105,121,139,147,155,171],"spectral":[9],"efficiency.":[10],"Meanwhile,":[11],"XL-MIMO":[12,27],"also":[13],"positions":[14],"communication":[16],"system":[17],"within":[18],"a":[19,61,78,130],"near-field":[20,28],"propagation":[21],"region.":[22],"In":[23,96],"this":[24],"paper,":[25],"localization":[29,158],"problem":[30,135],"is":[31,57,75,115,136,143],"broke":[32],"down":[33],"into":[34],"direction-of-arrival":[35],"(DOA)":[36],"estimation":[37,40],"and":[38,83,124,164],"distance":[39,128],"by":[41,85,146],"employing":[42],"virtual":[44],"far":[45],"field":[46],"model.":[47],"For":[48,127],"DoA":[49],"estimation,":[50,129],"off-grid":[52,73],"sparse":[53],"Bayesian":[54],"learning":[55],"(SBL)":[56],"used":[58],"together":[59],"with":[60,170],"covariance":[62],"error":[63,74],"matching":[64],"technique":[65],"to":[66,98,118],"improve":[67],"grid":[69,122],"refinement.":[70],"Specifically,":[71],"modeled":[76],"as":[77],"matrix":[79,88],"uncertainty":[80,89],"perturbation":[81],"problem,":[82],"solved":[84,145],"proposed":[87,117,156],"generalized":[90],"approximate":[91],"message":[92],"passing":[93],"(MUGAMP)":[94],"algorithm.":[95],"order":[97],"reduce":[99],"computational":[101,167],"complexity":[102,168],"arising":[103],"from":[104],"large-scale":[106],"antenna":[107],"array,":[108],"an":[109],"alternating":[110],"direction":[111],"GAMP":[112],"(ADGAMP)":[113],"algorithm":[114],"further":[116],"iteratively":[119],"optimize":[120],"mismatch":[123],"DOA":[125,140],"estimation.":[126,141],"spectrum":[131],"power":[132],"function":[133],"minimization":[134],"formulated":[137],"after":[138],"It":[142],"then":[144],"eigenvalue":[148],"decomposition":[149],"(EVD).":[150],"Simulation":[151],"results":[152],"demonstrate":[153],"that":[154],"ADGAMP+EVD":[157],"method":[159],"has":[160],"better":[161],"positioning":[162],"accuracy":[163],"exhibits":[165],"lower":[166],"compared":[169],"state-of-theart":[172],"methods.":[173]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}