{"id":"https://openalex.org/W7143424621","doi":"https://doi.org/10.48550/arxiv.2603.25754","title":"DUGC-VRNet: Joint VR Recognition and Channel Estimation for Spatially Non-Stationary XL-MIMO","display_name":"DUGC-VRNet: Joint VR Recognition and Channel Estimation for Spatially Non-Stationary XL-MIMO","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7143424621","doi":"https://doi.org/10.48550/arxiv.2603.25754"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25754","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25754","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.25754","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130659676","display_name":"Jinhao Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Jinhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031202162","display_name":"Guangchi Zhang","orcid":"https://orcid.org/0000-0001-8292-401X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Guangchi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074142957","display_name":"Miao Cui","orcid":"https://orcid.org/0000-0002-5947-7036"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Miao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130952628","display_name":"Hao Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130963488","display_name":"Xiaoli Chu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chu, Xiaoli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9228000044822693,"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":0.9228000044822693,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.026000000536441803,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.010700000450015068,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.7159000039100647},{"id":"https://openalex.org/keywords/visibility-graph","display_name":"Visibility graph","score":0.6777999997138977},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.619700014591217},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5830000042915344},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5533999800682068},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.520799994468689},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.436599999666214},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.41929998993873596}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.785099983215332},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.7159000039100647},{"id":"https://openalex.org/C173362246","wikidata":"https://www.wikidata.org/wiki/Q8216024","display_name":"Visibility graph","level":3,"score":0.6777999997138977},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.619700014591217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5927000045776367},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5830000042915344},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5533999800682068},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.520799994468689},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5148000121116638},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.41929998993873596},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3919999897480011},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35899999737739563},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2784999907016754},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25690001249313354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25754","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25754","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.25754","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25754","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"we":[3,66,125],"address":[4],"spatially":[5,154],"non-stationary":[6,155],"near-field":[7],"channel":[8,33,64,116,146],"estimation":[9,34,56,117,147],"for":[10],"extremely":[11],"large-scale":[12],"multiple-input":[13],"multiple-output":[14],"(XL-MIMO)":[15],"systems":[16],"with":[17,73],"a":[18,68,74,81,131],"hybrid":[19],"combining":[20],"architecture.":[21],"One":[22],"key":[23],"challenge":[24],"in":[25,30],"the":[26,44,95,99,110,138],"considered":[27],"problem":[28],"lies":[29],"that":[31,137],"conventional":[32],"algorithms":[35],"typically":[36],"struggle":[37],"to":[38,43,80,107,129],"effectively":[39],"identify":[40],"and":[41,63,84,102,140,148],"adapt":[42],"partial":[45],"antenna":[46],"visibility":[47,51],"caused":[48],"by":[49],"varying":[50],"regions":[52],"(VRs),":[53],"thereby":[54,113],"compromising":[55],"accuracy.":[57],"To":[58,121],"perform":[59],"joint":[60],"VR":[61,105,151],"recognition":[62,152],"estimation,":[65],"integrate":[67],"deep":[69],"unfolding":[70],"network":[71,77],"(DUN)":[72],"graph":[75,97],"convolution":[76],"(GCN),":[78],"leading":[79],"Deep":[82],"Unfolding":[83],"Graph":[85],"Convolution":[86],"coupled,":[87],"Visibility":[88],"Region":[89],"Aware":[90],"Network":[91],"(DUGC-VRNet).":[92],"By":[93],"leveraging":[94],"channel's":[96],"structure,":[98],"GCN":[100],"infers":[101],"feeds":[103],"back":[104],"information":[106],"dynamically":[108],"guide":[109],"DUN's":[111],"updates,":[112],"enhancing":[114],"reliable":[115],"under":[118,153],"spatial":[119],"non-stationarity.":[120],"reduce":[122],"DUGC-VRNet's":[123],"complexity,":[124],"apply":[126],"weight":[127],"pruning":[128],"obtain":[130],"lightweight":[132],"network.":[133],"Simulation":[134],"results":[135],"demonstrate":[136],"DUGC-VRNet":[139],"its":[141],"pruned":[142],"variant":[143],"achieve":[144],"superior":[145],"more":[149],"accurate":[150],"conditions.":[156]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-31T00:00:00"}