{"id":"https://openalex.org/W4414110623","doi":"https://doi.org/10.1109/twc.2025.3605521","title":"Auxiliary Bayesian Learning Approach for Joint Channel Estimation and Data Detection With RIS-Assisted OFDM Systems","display_name":"Auxiliary Bayesian Learning Approach for Joint Channel Estimation and Data Detection With RIS-Assisted OFDM Systems","publication_year":2025,"publication_date":"2025-09-10","ids":{"openalex":"https://openalex.org/W4414110623","doi":"https://doi.org/10.1109/twc.2025.3605521"},"language":"en","primary_location":{"id":"doi:10.1109/twc.2025.3605521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2025.3605521","pdf_url":null,"source":{"id":"https://openalex.org/S63459445","display_name":"IEEE Transactions on Wireless Communications","issn_l":"1536-1276","issn":["1536-1276","1558-2248"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Wireless Communications","raw_type":"journal-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/A5101477864","display_name":"Chen Ji","orcid":"https://orcid.org/0000-0002-5434-420X"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Ji","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032700528","display_name":"Jisheng Dai","orcid":"https://orcid.org/0000-0002-0462-4414"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jisheng Dai","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061105504","display_name":"Xueqin Jiang","orcid":"https://orcid.org/0000-0002-0414-4349"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue-Qin Jiang","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061152961","display_name":"Weichao Xu","orcid":"https://orcid.org/0000-0001-6516-0927"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weichao Xu","raw_affiliation_strings":["Department of Automatic Control, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Automatic Control, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101477864"],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27571276,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":null,"first_page":"3705","last_page":"3720"},"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":0.9853000044822693,"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":0.9853000044822693,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9801999926567078,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9743000268936157,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/message-passing","display_name":"Message passing","score":0.5924999713897705},{"id":"https://openalex.org/keywords/orthogonal-frequency-division-multiplexing","display_name":"Orthogonal frequency-division multiplexing","score":0.5633000135421753},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5322999954223633},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4959999918937683},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4745999872684479},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.45170000195503235},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4277999997138977},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.40400001406669617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8070999979972839},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.5924999713897705},{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.5633000135421753},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5322999954223633},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4959999918937683},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4745999872684479},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.45170000195503235},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.40400001406669617},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3856000006198883},{"id":"https://openalex.org/C32409245","wikidata":"https://www.wikidata.org/wiki/Q749753","display_name":"Quadrature amplitude modulation","level":4,"score":0.376800000667572},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36329999566078186},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.35839998722076416},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3328000009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32580000162124634},{"id":"https://openalex.org/C101765175","wikidata":"https://www.wikidata.org/wiki/Q577764","display_name":"Communications system","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C159246509","wikidata":"https://www.wikidata.org/wiki/Q5428725","display_name":"Factor graph","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2522999942302704},{"id":"https://openalex.org/C86426650","wikidata":"https://www.wikidata.org/wiki/Q7452504","display_name":"Sequential estimation","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/twc.2025.3605521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2025.3605521","pdf_url":null,"source":{"id":"https://openalex.org/S63459445","display_name":"IEEE Transactions on Wireless Communications","issn_l":"1536-1276","issn":["1536-1276","1558-2248"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Wireless Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1510028821","https://openalex.org/W1763302039","https://openalex.org/W1959879694","https://openalex.org/W2014933333","https://openalex.org/W2037293229","https://openalex.org/W2254069717","https://openalex.org/W2272774410","https://openalex.org/W2945463326","https://openalex.org/W2952909243","https://openalex.org/W2971912794","https://openalex.org/W2994742101","https://openalex.org/W3001370401","https://openalex.org/W3008356568","https://openalex.org/W3011747750","https://openalex.org/W3035386068","https://openalex.org/W3039790476","https://openalex.org/W3104071687","https://openalex.org/W3118629792","https://openalex.org/W3133613115","https://openalex.org/W3135614874","https://openalex.org/W3144244478","https://openalex.org/W3155222786","https://openalex.org/W3196529033","https://openalex.org/W3198789116","https://openalex.org/W3199775031","https://openalex.org/W4210442158","https://openalex.org/W4210551079","https://openalex.org/W4210680740","https://openalex.org/W4211052011","https://openalex.org/W4212980349","https://openalex.org/W4214571564","https://openalex.org/W4214867678","https://openalex.org/W4285142136","https://openalex.org/W4312398668","https://openalex.org/W4312866655","https://openalex.org/W4318141576","https://openalex.org/W4319866159","https://openalex.org/W4320000069","https://openalex.org/W4323346131","https://openalex.org/W4323530235","https://openalex.org/W4362714745","https://openalex.org/W4367359450","https://openalex.org/W4378697019","https://openalex.org/W4378697233","https://openalex.org/W4380520376","https://openalex.org/W4385284018","https://openalex.org/W4386025740","https://openalex.org/W4389371447","https://openalex.org/W4394811136","https://openalex.org/W4394939036","https://openalex.org/W4398152817","https://openalex.org/W4399341548","https://openalex.org/W4399405741","https://openalex.org/W4403758851"],"related_works":["https://openalex.org/W2792339401","https://openalex.org/W2530747331","https://openalex.org/W3097525855","https://openalex.org/W2125564215","https://openalex.org/W4391741972","https://openalex.org/W1986382998","https://openalex.org/W2517776947","https://openalex.org/W2084482193","https://openalex.org/W2972611783","https://openalex.org/W4243590696"],"abstract_inverted_index":{"Joint":[0],"channel":[1,86],"estimation":[2,87],"and":[3,16,49,88,104,127,170,173,191],"data":[4,47,89,128],"detection":[5,90],"can":[6],"enhance":[7],"the":[8,27,38,76,111,132],"performance":[9],"of":[10,29,40,110,157],"both":[11],"tasks,":[12],"improve":[13],"communication":[14],"efficiency,":[15],"reduce":[17],"pilot":[18,126],"overhead.":[19],"However,":[20],"this":[21,74],"has":[22],"been":[23],"rarely":[24],"explored":[25],"in":[26],"context":[28],"reconfigurable":[30],"intelligent":[31],"surface":[32],"(RIS)-assisted":[33],"OFDM":[34,93],"systems":[35,65],"due":[36],"to":[37,99,123,166,180],"complexity":[39,169],"handling":[41],"multiple":[42],"coupling":[43],"effects":[44],"between":[45],"various":[46,161],"sequences":[48],"reflection":[50],"coefficients.":[51],"The":[52,108],"recently":[53],"proposed":[54,112],"solution":[55],"is":[56],"tailored":[57],"for":[58,84,154],"purely":[59],"phase":[60],"modulations,":[61],"whereas":[62],"modern":[63],"5G/6G":[64],"predominantly":[66],"use":[67],"quadrature":[68],"amplitude":[69],"modulation":[70,143],"(QAM).":[71],"To":[72],"overcome":[73],"limitation,":[75],"paper":[77],"proposes":[78],"an":[79,118],"auxiliary":[80,119],"Bayesian":[81,120,158],"learning":[82,121],"approach":[83,153],"joint":[85],"with":[91,160],"RIS-assisted":[92],"systems,":[94],"which":[95],"integrates":[96],"advanced":[97],"techniques":[98],"offer":[100],"robustness,":[101],"improved":[102],"performance,":[103],"reduced":[105],"computational":[106,168],"complexity.":[107],"novelties":[109],"method":[113],"are":[114],"threefold:":[115],"i)":[116],"present":[117],"framework":[122],"probabilistically":[124],"link":[125],"information,":[129],"effectively":[130],"formulating":[131],"common":[133],"sparsity":[134],"pattern":[135],"while":[136],"avoiding":[137],"potential":[138],"modeling":[139],"errors":[140],"introduced":[141],"by":[142],"schemes;":[144],"ii)":[145],"derive":[146],"a":[147,176],"hybrid":[148],"approximate":[149],"message":[150,183,187],"passing":[151,188],"(AMP)":[152],"efficient":[155,186],"execution":[156],"inference,":[159],"approximation":[162,171],"strategies":[163],"seamlessly":[164],"integrated":[165],"balance":[167],"accuracy;":[172],"iii)":[174],"embed":[175],"novel":[177],"rearrangement":[178],"strategy":[179],"streamline":[181],"multilayer":[182],"extraction,":[184],"facilitating":[185],"among":[189],"sub-modules":[190],"subsequent":[192],"parameter":[193],"learning.":[194],"Simulation":[195],"results":[196],"demonstrate":[197],"its":[198],"superiority.":[199]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}