{"id":"https://openalex.org/W4408357858","doi":"https://doi.org/10.1109/twc.2025.3547705","title":"GNN-Based Structured Bayesian Inference for Multi-Grid Localized Statistical Channel Modeling","display_name":"GNN-Based Structured Bayesian Inference for Multi-Grid Localized Statistical Channel Modeling","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408357858","doi":"https://doi.org/10.1109/twc.2025.3547705"},"language":"en","primary_location":{"id":"doi:10.1109/twc.2025.3547705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2025.3547705","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":null,"display_name":"Yiheng Wang","orcid":"https://orcid.org/0009-0006-5129-889X"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiheng Wang","raw_affiliation_strings":["Shenzhen Research Institute of Big Data, School of Data Science, The Chinese University of Hong Kong at Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0006-5129-889X","affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data, School of Data Science, The Chinese University of Hong Kong at Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077991508","display_name":"Ye Xue","orcid":"https://orcid.org/0000-0001-9629-8996"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Xue","raw_affiliation_strings":["Shenzhen Research Institute of Big Data, School of Data Science, The Chinese University of Hong Kong at Shenzhen, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data, School of Data Science, The Chinese University of Hong Kong at Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000618158","display_name":"Shutao Zhang","orcid":"https://orcid.org/0000-0002-2131-5883"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutao Zhang","raw_affiliation_strings":["School of Science and Engineering, Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong at Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-2131-5883","affiliations":[{"raw_affiliation_string":"School of Science and Engineering, Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong at Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064271996","display_name":"Tsung\u2010Hui Chang","orcid":"https://orcid.org/0000-0003-1349-2764"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tsung-Hui Chang","raw_affiliation_strings":["School of Science and Engineering, Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong at Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-1349-2764","affiliations":[{"raw_affiliation_string":"School of Science and Engineering, Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong at Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8098,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.92622444,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"24","issue":"7","first_page":"5508","last_page":"5524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9980000257492065,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9976999759674072,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7377078533172607},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5715965628623962},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5569769144058228},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.532869815826416},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4855925440788269},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4833247661590576},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.45263564586639404},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.42498868703842163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3923463821411133},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36391639709472656},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1725597083568573},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14886581897735596},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11012908816337585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7377078533172607},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5715965628623962},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5569769144058228},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.532869815826416},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4855925440788269},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4833247661590576},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.45263564586639404},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.42498868703842163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3923463821411133},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36391639709472656},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1725597083568573},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14886581897735596},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11012908816337585},{"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/twc.2025.3547705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2025.3547705","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":[{"id":"https://openalex.org/G5803679919","display_name":null,"funder_award_id":"62301334","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7719467863","display_name":null,"funder_award_id":"2023YFB2904804","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329841","display_name":"Guangdong Provincial Key Laboratory of Construction Foundation","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1997834106","https://openalex.org/W2000721204","https://openalex.org/W2018643445","https://openalex.org/W2024635814","https://openalex.org/W2098841537","https://openalex.org/W2113328646","https://openalex.org/W2126759246","https://openalex.org/W2129131372","https://openalex.org/W2136634080","https://openalex.org/W2139701068","https://openalex.org/W2146000945","https://openalex.org/W2150859678","https://openalex.org/W2169030369","https://openalex.org/W2520000847","https://openalex.org/W2591962042","https://openalex.org/W2777046509","https://openalex.org/W2883649322","https://openalex.org/W2900841156","https://openalex.org/W2907492528","https://openalex.org/W2911643182","https://openalex.org/W2913596349","https://openalex.org/W2963290405","https://openalex.org/W2975873504","https://openalex.org/W2983079747","https://openalex.org/W3006668132","https://openalex.org/W3044954276","https://openalex.org/W3111885788","https://openalex.org/W3133902371","https://openalex.org/W3152787073","https://openalex.org/W3167779900","https://openalex.org/W3211830369","https://openalex.org/W4221150253","https://openalex.org/W4244155866","https://openalex.org/W4283717304","https://openalex.org/W4288574671","https://openalex.org/W4297825594","https://openalex.org/W4300516455","https://openalex.org/W4309270034","https://openalex.org/W4376478381","https://openalex.org/W4379382365","https://openalex.org/W4381162639","https://openalex.org/W4391827352","https://openalex.org/W4402157153","https://openalex.org/W6674632333","https://openalex.org/W6676664377","https://openalex.org/W6696497002","https://openalex.org/W6759127422","https://openalex.org/W6762445188"],"related_works":["https://openalex.org/W137830373","https://openalex.org/W3000984192","https://openalex.org/W2103073163","https://openalex.org/W4286952477","https://openalex.org/W4321348134","https://openalex.org/W4387929287","https://openalex.org/W2372267530","https://openalex.org/W2795206833","https://openalex.org/W2969189870","https://openalex.org/W3183730129"],"abstract_inverted_index":{"Localized":[0],"statistical":[1],"channel":[2,8,27,116],"modeling":[3,9],"(LSCM)":[4],"is":[5,40],"an":[6,178],"efficient":[7],"framework":[10],"recently":[11],"proposed":[12,193],"for":[13,87,172],"wireless":[14,60],"network":[15,99],"optimization":[16],"which":[17],"learns":[18],"the":[19,25,29,37,53,71,88,92,111,115,127,133,138,154,167,170,187,192],"angular":[20],"power":[21,34],"spectrum":[22],"(APS)":[23],"of":[24,56,76,129,135,158,169,191],"downlink":[26],"from":[28,46],"beam-wise":[30],"reference":[31],"signal":[32],"receiving":[33],"(RSRP).":[35],"However,":[36],"conventional":[38,145],"LSCM":[39,72],"only":[41],"based":[42],"on":[43],"RSRP":[44],"measurements":[45],"one":[47],"single":[48],"geographical":[49,78],"grid":[50],"and":[51,80,118,163,189],"ignores":[52],"inherent":[54],"property":[55],"spatial":[57],"consistency":[58],"over":[59],"channels,":[61],"resulting":[62],"in":[63,73,114,144],"suboptimal":[64],"performance.":[65],"To":[66,165],"this":[67],"end,":[68],"we":[69,152,176],"consider":[70],"a":[74,83,104],"manner":[75],"multiple":[77,130],"grids":[79],"further":[81],"propose":[82,177],"novel":[84],"graph-based":[85],"approach":[86],"multi-grid":[89],"LSCM,":[90],"called":[91],"accelerated":[93],"Markovian":[94,106],"variational":[95,121],"Bayesian":[96,122],"graph":[97,107],"neural":[98],"(AMVB-GNN).":[100],"The":[101],"AMVB-GNN":[102,136,194],"leverages":[103],"heterogeneous":[105],"representation":[108],"to":[109,125],"capture":[110],"structured":[112],"sparsity":[113],"APSs":[117,128,174],"employs":[119],"refined":[120],"inference":[123],"(VBI)":[124],"learn":[126],"grids.":[131],"Notably,":[132],"design":[134],"eliminates":[137],"exact":[139],"matrix":[140],"inversion":[141],"operations":[142],"required":[143],"VBI,":[146],"thereby":[147],"enhancing":[148],"computational":[149],"efficiency.":[150],"Additionally,":[151],"demonstrate":[153],"partial":[155],"permutation":[156],"equivalence":[157],"AMVB-GNN,":[159],"ensuring":[160],"both":[161],"interpretability":[162],"reliability.":[164],"address":[166],"issue":[168],"demand":[171],"ground-truth":[173],"labels,":[175],"unsupervised":[179],"training":[180],"loss":[181],"function.":[182],"Extensive":[183],"simulation":[184],"experiments":[185],"validate":[186],"effectiveness":[188],"efficiency":[190],"model.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
