{"id":"https://openalex.org/W3212564261","doi":"https://doi.org/10.1109/istc49272.2021.9594204","title":"Multiuser MIMO Detection With Composite NUV Priors","display_name":"Multiuser MIMO Detection With Composite NUV Priors","publication_year":2021,"publication_date":"2021-08-30","ids":{"openalex":"https://openalex.org/W3212564261","doi":"https://doi.org/10.1109/istc49272.2021.9594204","mag":"3212564261"},"language":"en","primary_location":{"id":"doi:10.1109/istc49272.2021.9594204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/istc49272.2021.9594204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 11th International Symposium on Topics in Coding (ISTC)","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/A5004587877","display_name":"Gian Marti","orcid":"https://orcid.org/0000-0001-6848-0213"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Gian Marti","raw_affiliation_strings":["ETH Zurich"],"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045014911","display_name":"Raphael Keusch","orcid":"https://orcid.org/0000-0001-5790-6709"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Raphael Keusch","raw_affiliation_strings":["ETH Zurich"],"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051479034","display_name":"Hans\u2010Andrea Loeliger","orcid":"https://orcid.org/0000-0001-7153-7145"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Hans-Andrea Loeliger","raw_affiliation_strings":["ETH Zurich"],"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004587877"],"corresponding_institution_ids":["https://openalex.org/I35440088"],"apc_list":null,"apc_paid":null,"fwci":0.1528,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52538136,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9965999722480774,"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"}},"topics":[{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9965999722480774,"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":0.9962000250816345,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9864000082015991,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.8907783031463623},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6064768433570862},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5766860842704773},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5315613150596619},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5211136937141418},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44181883335113525},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.43063998222351074},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39179152250289917},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3250167667865753},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2893376052379608},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06291180849075317},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.061010271310806274}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8907783031463623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6064768433570862},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5766860842704773},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5315613150596619},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5211136937141418},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44181883335113525},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43063998222351074},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39179152250289917},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3250167667865753},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2893376052379608},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06291180849075317},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.061010271310806274},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/istc49272.2021.9594204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/istc49272.2021.9594204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 11th International Symposium on Topics in Coding (ISTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2052963087","https://openalex.org/W2054877413","https://openalex.org/W2100440346","https://openalex.org/W2129893919","https://openalex.org/W2141974809","https://openalex.org/W2148154358","https://openalex.org/W2166500259","https://openalex.org/W2550997788","https://openalex.org/W2758999846","https://openalex.org/W2914510817","https://openalex.org/W2963372284","https://openalex.org/W2963895729","https://openalex.org/W3047573666","https://openalex.org/W3157482577","https://openalex.org/W3160750193","https://openalex.org/W4287184762","https://openalex.org/W6793943726"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W2562263695","https://openalex.org/W2135187896","https://openalex.org/W2147201983","https://openalex.org/W2015518264","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W2017034551"],"abstract_inverted_index":{"Normals":[0],"with":[1],"unknown":[2],"variances":[3],"(NUV)":[4],"representations":[5,8],"encompass":[6],"variational":[7],"of":[9],"sparsifying":[10],"norms":[11],"and":[12,26,42,74],"priors":[13],"for":[14,48],"sparse":[15],"Bayesian":[16],"learning.":[17],"Recently,":[18],"a":[19,79],"binarizing":[20],"NUV":[21],"prior":[22,41],"has":[23],"been":[24],"proposed":[25],"shown":[27],"to":[28,44,56],"work":[29],"very":[30],"well":[31],"on":[32,38,71,82],"certain":[33],"approximation":[34],"problems.":[35,50],"We":[36],"elaborate":[37],"this":[39],"new":[40],"begin":[43],"explore":[45],"its":[46],"use":[47],"recovery":[49],"Concretely,":[51],"we":[52],"apply":[53],"the":[54,57,65],"method":[55,66,80],"multiuser":[58],"multiple-input":[59],"multiple-output":[60],"(MIMO)":[61],"detection":[62],"problem.":[63],"Empirically,":[64],"outperforms":[67],"existing":[68],"approaches":[69],"based":[70,81],"convex":[72],"relaxations":[73],"is":[75],"more":[76],"robust":[77],"than":[78],"approximate":[83],"message-passing.":[84]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}