{"id":"https://openalex.org/W4400277714","doi":"https://doi.org/10.1109/wcnc57260.2024.10570782","title":"Learning the Discrete Maximum a Posteriori Distribution for Soft MIMO Detection","display_name":"Learning the Discrete Maximum a Posteriori Distribution for Soft MIMO Detection","publication_year":2024,"publication_date":"2024-04-21","ids":{"openalex":"https://openalex.org/W4400277714","doi":"https://doi.org/10.1109/wcnc57260.2024.10570782"},"language":"en","primary_location":{"id":"doi:10.1109/wcnc57260.2024.10570782","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wcnc57260.2024.10570782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Wireless Communications and Networking Conference (WCNC)","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/A5086844015","display_name":"Jiankun Zhang","orcid":"https://orcid.org/0000-0001-7832-5268"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiankun Zhang","raw_affiliation_strings":["Huawei Technologies Co., Ltd,Beijing,China,100095"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd,Beijing,China,100095","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100599817","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0003-0896-080X"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Huawei Technologies Co., Ltd,Beijing,China,100095"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd,Beijing,China,100095","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443879","display_name":"Yan Li","orcid":"https://orcid.org/0000-0002-4694-4926"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["Huawei Technologies Co., Ltd,Xi&#x0027;an,Shaanxi,China,710075"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd,Xi&#x0027;an,Shaanxi,China,710075","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052597621","display_name":"Jing Qian","orcid":"https://orcid.org/0000-0002-2047-6917"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Qian","raw_affiliation_strings":["Huawei Technologies Co., Ltd,Beijing,China,100095"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd,Beijing,China,100095","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2250955327"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9754999876022339,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9754999876022339,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9656000137329102,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9528999924659729,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.7605689764022827},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.6347693204879761},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.565095067024231},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5564289689064026},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.4162823557853699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32595664262771606},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27355581521987915},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2364950180053711},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1286759078502655},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.11521023511886597}],"concepts":[{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.7605689764022827},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.6347693204879761},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.565095067024231},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5564289689064026},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.4162823557853699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32595664262771606},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27355581521987915},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2364950180053711},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1286759078502655},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.11521023511886597},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcnc57260.2024.10570782","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wcnc57260.2024.10570782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Wireless Communications and Networking Conference (WCNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1992036418","https://openalex.org/W2022148313","https://openalex.org/W2050308627","https://openalex.org/W2082029531","https://openalex.org/W2112059973","https://openalex.org/W2120577497","https://openalex.org/W2127401968","https://openalex.org/W2160897074","https://openalex.org/W2596893449","https://openalex.org/W2783260097","https://openalex.org/W2804075771","https://openalex.org/W2964163499","https://openalex.org/W3008026851","https://openalex.org/W3047911146","https://openalex.org/W3098966377","https://openalex.org/W4293057676","https://openalex.org/W4315630161"],"related_works":["https://openalex.org/W1503532423","https://openalex.org/W2150865841","https://openalex.org/W1967494390","https://openalex.org/W2138865713","https://openalex.org/W3013496002","https://openalex.org/W2169353922","https://openalex.org/W2465363361","https://openalex.org/W2896820906","https://openalex.org/W2101542441","https://openalex.org/W4284711868"],"abstract_inverted_index":{"The":[0],"maximum":[1],"a":[2,25,38,66],"posteriori":[3],"(MAP)":[4],"detector":[5],"is":[6,19,48],"widely":[7],"regarded":[8],"as":[9],"the":[10,44,50,57,60,73,83,90,109,114,121,125],"optimal":[11,126],"one":[12],"for":[13],"soft":[14,39],"multiple-input-multiple-output":[15],"(MIMO)":[16],"detection,":[17],"but":[18],"infeasible":[20],"to":[21,29,118,124],"be":[22,99],"used":[23],"in":[24],"practical":[26],"system":[27],"due":[28],"its":[30],"prohibitive":[31],"cost.":[32],"In":[33],"this":[34],"paper,":[35],"we":[36,55,80],"propose":[37],"MIMO":[40],"detection":[41],"theory":[42],"approaching":[43],"MAP":[45,127],"performance,":[46],"which":[47],"called":[49],"MAP-moment":[51],"(MAPM)":[52],"algorithm.":[53],"First,":[54],"fit":[56],"moments":[58],"of":[59,69,75,120],"discrete":[61],"joint":[62],"posterior":[63,86],"probability":[64,87],"with":[65,72],"small":[67],"number":[68],"observations.":[70],"Then,":[71],"help":[74],"deep":[76],"unfolded":[77],"Riemann-theta":[78],"function,":[79],"can":[81,98,112],"learn":[82],"true":[84],"marginal":[85],"distribution":[88],"from":[89],"aforementioned":[91],"moments.":[92],"Finally,":[93],"bit":[94],"log-likelihood":[95],"ratios":[96],"(LLRs)":[97],"precisely":[100],"derived":[101],"by":[102],"simple":[103],"calculation.":[104],"Simulation":[105],"results":[106],"indicate":[107],"that":[108],"proposed":[110],"algorithm":[111],"improve":[113],"performance":[115],"significantly":[116],"compared":[117],"State":[119],"Art,":[122],"close":[123],"detector.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
