{"id":"https://openalex.org/W7124421517","doi":"https://doi.org/10.1109/lsp.2026.3654532","title":"On the Asymptotic MSE-Optimality of Parametric Bayesian Channel Estimation in mmWave Systems","display_name":"On the Asymptotic MSE-Optimality of Parametric Bayesian Channel Estimation in mmWave Systems","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7124421517","doi":"https://doi.org/10.1109/lsp.2026.3654532"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2026.3654532","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3654532","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/lsp.2026.3654532","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074327006","display_name":"Franz Wei\u00dfer","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Franz Wei\u00dfer","raw_affiliation_strings":["TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123230976","display_name":"Wolfgang Utschick","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Utschick","raw_affiliation_strings":["TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074327006"],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24285661,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"653","last_page":"657"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.7419000267982483,"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":0.7419000267982483,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.10440000146627426,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.09610000252723694,"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/estimator","display_name":"Estimator","score":0.7853000164031982},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6510999798774719},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.583899974822998},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5741999745368958},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5730999708175659},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.5393999814987183},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4526999890804291}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7853000164031982},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6510999798774719},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.583899974822998},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5755000114440918},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5741999745368958},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5730999708175659},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.5393999814987183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48559999465942383},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4526999890804291},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4465999901294708},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44359999895095825},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4187999963760376},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.41429999470710754},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.3946000039577484},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.36039999127388},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.33480000495910645},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32749998569488525},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3167000114917755},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2669000029563904}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2026.3654532","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3654532","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/lsp.2026.3654532","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3654532","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1952629836","https://openalex.org/W2096710051","https://openalex.org/W2113638573","https://openalex.org/W2123331874","https://openalex.org/W2130700086","https://openalex.org/W2138017653","https://openalex.org/W2141658588","https://openalex.org/W2157638198","https://openalex.org/W2501970484","https://openalex.org/W2738538347","https://openalex.org/W2770606349","https://openalex.org/W3048912828","https://openalex.org/W3134264804","https://openalex.org/W4254782144","https://openalex.org/W4288072110","https://openalex.org/W4403182726","https://openalex.org/W4408354663"],"related_works":[],"abstract_inverted_index":{"The":[0],"mean":[1,12],"square":[2],"error":[3],"(MSE)-optimal":[4],"estimator":[5,13],"is":[6,70],"known":[7],"to":[8,34],"be":[9],"the":[10,30,36,57,93],"conditional":[11],"(CME).":[14],"This":[15,27],"paper":[16],"introduces":[17],"a":[18,51],"parametric":[19,66],"channel":[20,32,39,58,68],"estimation":[21,69],"technique":[22,28],"based":[23],"on":[24,56,61],"Bayesian":[25,67],"estimation.":[26],"uses":[29],"estimated":[31],"parameters":[33],"parameterize":[35],"well-known":[37],"LMMSE":[38],"estimator.":[40],"We":[41],"first":[42],"derive":[43],"an":[44],"asymptotic":[45],"CME":[46],"formulation":[47],"that":[48,65],"holds":[49],"for":[50,72],"wide":[52],"range":[53],"of":[54],"priors":[55],"parameters.":[59],"Based":[60],"this,":[62],"we":[63],"show":[64],"MSE-optimal":[71],"high":[73],"signal-to-noise":[74],"ratio":[75],"(SNR)":[76],"and/or":[77],"long":[78],"coherence":[79,88],"intervals,":[80],"i.e.,":[81],"many":[82],"noisy":[83],"observations":[84],"provided":[85],"within":[86],"one":[87],"interval.":[89],"Numerical":[90],"simulations":[91],"validate":[92],"derived":[94],"formulations.":[95]},"counts_by_year":[],"updated_date":"2026-01-29T23:13:10.619473","created_date":"2026-01-17T00:00:00"}
