{"id":"https://openalex.org/W4409156565","doi":"https://doi.org/10.1109/ieeeconf60004.2024.10942808","title":"Fast and Robust Expectation Propagation MIMO Detection via Preconditioned Conjugated Gradient","display_name":"Fast and Robust Expectation Propagation MIMO Detection via Preconditioned Conjugated Gradient","publication_year":2024,"publication_date":"2024-10-27","ids":{"openalex":"https://openalex.org/W4409156565","doi":"https://doi.org/10.1109/ieeeconf60004.2024.10942808"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf60004.2024.10942808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf60004.2024.10942808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 58th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-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/A5047833670","display_name":"Luca Schmid","orcid":"https://orcid.org/0000-0003-1236-5253"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Luca Schmid","raw_affiliation_strings":["Karlsruhe Institute of Technology,Communications Engineering Lab,Karlsruhe,Germany,76187"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology,Communications Engineering Lab,Karlsruhe,Germany,76187","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095900472","display_name":"Dominik Sulz","orcid":null},"institutions":[{"id":"https://openalex.org/I143910747","display_name":"TH Bingen University of Applied Sciences","ror":"https://ror.org/01pxkj057","country_code":"DE","type":"education","lineage":["https://openalex.org/I143910747"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dominik Sulz","raw_affiliation_strings":["Mathematical Institute, University of Tübingen,Tübingen,Germany,72076"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mathematical Institute, University of Tübingen,Tübingen,Germany,72076","institution_ids":["https://openalex.org/I143910747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053280913","display_name":"Laurent Schmalen","orcid":"https://orcid.org/0000-0002-1459-9128"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Laurent Schmalen","raw_affiliation_strings":["Karlsruhe Institute of Technology,Communications Engineering Lab,Karlsruhe,Germany,76187"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology,Communications Engineering Lab,Karlsruhe,Germany,76187","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.986,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73665668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1603","last_page":"1608"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.987500011920929,"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":0.987500011920929,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9812999963760376,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9782000184059143,"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/mimo","display_name":"MIMO","score":0.5494130253791809},{"id":"https://openalex.org/keywords/conjugated-system","display_name":"Conjugated system","score":0.499439001083374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4893791079521179},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1979106366634369},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.18537738919258118}],"concepts":[{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5494130253791809},{"id":"https://openalex.org/C112613896","wikidata":"https://www.wikidata.org/wiki/Q898370","display_name":"Conjugated system","level":3,"score":0.499439001083374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4893791079521179},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1979106366634369},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.18537738919258118},{"id":"https://openalex.org/C521977710","wikidata":"https://www.wikidata.org/wiki/Q81163","display_name":"Polymer","level":2,"score":0.0},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf60004.2024.10942808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf60004.2024.10942808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 58th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1992036418","https://openalex.org/W2015142990","https://openalex.org/W2052321444","https://openalex.org/W2074780612","https://openalex.org/W2075505133","https://openalex.org/W2139317044","https://openalex.org/W2148551624","https://openalex.org/W2316564661","https://openalex.org/W2778503646","https://openalex.org/W2906686309","https://openalex.org/W2948226226","https://openalex.org/W2954228593","https://openalex.org/W3031023929","https://openalex.org/W3179042490","https://openalex.org/W4212863985","https://openalex.org/W4285742293","https://openalex.org/W4312258136","https://openalex.org/W6611576299","https://openalex.org/W6640231202"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2035358533","https://openalex.org/W2958772852","https://openalex.org/W2400254448","https://openalex.org/W2078259192","https://openalex.org/W2060215961","https://openalex.org/W2090854855","https://openalex.org/W2957149672"],"abstract_inverted_index":{"We":[0,47,70],"study":[1,71],"the":[2,31,53,60,72,79,85,93,100,106,118,125,136,139,151,161],"expectation":[3],"propagation":[4],"(EP)":[5],"algorithm":[6,55,76],"for":[7,77],"symbol":[8],"detection":[9],"in":[10,35,155],"massive":[11],"multiple-input":[12],"multiple-output":[13],"(MIMO)":[14],"systems.":[15],"The":[16],"EP":[17,37,54,101,153],"detector":[18,154],"shows":[19],"excellent":[20],"per-formance":[21],"but":[22],"suffers":[23],"from":[24],"a":[25,44,110,130],"high":[26,156],"computational":[27],"complexity":[28,86],"due":[29],"to":[30,39,98],"matrix":[32,162],"inversion,":[33],"required":[34],"each":[36],"iteration":[38],"perform":[40],"marginal":[41],"inference":[42,58,158],"on":[43,59,92,114,124,129],"Gaussian":[45],"system.":[46],"propose":[48],"an":[49,144],"inversion-free":[50],"variant":[51],"of":[52,117,138],"by":[56,90],"treating":[57],"mean":[61],"and":[62,67,87,128,148],"variance":[63],"as":[64],"two":[65],"separate":[66],"simpler":[68],"subtasks:":[69],"preconditioned":[73],"conjugate":[74],"gradient":[75],"obtaining":[78],"mean,":[80],"which":[81,142],"can":[82],"significantly":[83],"reduce":[84],"increase":[88],"stability":[89],"relying":[91],"Jacobi":[94],"preconditioner":[95],"that":[96],"proves":[97],"fit":[99],"characteristics":[102],"very":[103],"well.":[104],"For":[105],"variance,":[107],"we":[108],"use":[109],"simple":[111],"approximation":[112],"based":[113],"linear":[115],"regression":[116],"Gram":[119],"channel":[120,127,133],"matrix.":[121],"Numerical":[122],"studies":[123],"Rayleigh-fading":[126],"realistic":[131],"3GPP":[132],"model":[134],"reveal":[135],"efficiency":[137],"proposed":[140],"scheme,":[141],"offers":[143],"attractive":[145],"performance-complexity":[146],"tradeoff":[147],"even":[149],"outperforms":[150],"original":[152],"multi-user":[157],"cases":[159],"where":[160],"inversion":[163],"becomes":[164],"numerically":[165],"unstable.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}