{"id":"https://openalex.org/W4399206500","doi":"https://doi.org/10.1109/lwc.2024.3407813","title":"DARENet: Data Arrangement Neural Network for Eigenvector-Based CSI Feedback","display_name":"DARENet: Data Arrangement Neural Network for Eigenvector-Based CSI Feedback","publication_year":2024,"publication_date":"2024-05-31","ids":{"openalex":"https://openalex.org/W4399206500","doi":"https://doi.org/10.1109/lwc.2024.3407813"},"language":"en","primary_location":{"id":"doi:10.1109/lwc.2024.3407813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2024.3407813","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"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 Wireless Communications Letters","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/A5064211964","display_name":"Ruofei Gao","orcid":"https://orcid.org/0009-0001-6750-1550"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruofei Gao","raw_affiliation_strings":["Department of Internet of Things Technology and Application, China Mobile Research Institute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Internet of Things Technology and Application, China Mobile Research Institute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071987984","display_name":"Xiaotao Li","orcid":"https://orcid.org/0000-0001-8786-2962"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotao Li","raw_affiliation_strings":["Department of Internet of Things Technology and Application, China Mobile Research Institute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Internet of Things Technology and Application, China Mobile Research Institute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102986531","display_name":"Wai Chen","orcid":"https://orcid.org/0000-0002-1663-2729"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wai Chen","raw_affiliation_strings":["Department of Internet of Things Technology and Application, China Mobile Research Institute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Internet of Things Technology and Application, China Mobile Research Institute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5064211964"],"corresponding_institution_ids":["https://openalex.org/I180662265"],"apc_list":null,"apc_paid":null,"fwci":1.4176,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.8380429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"13","issue":"8","first_page":"2215","last_page":"2219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9994999766349792,"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":0.9994999766349792,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9973000288009644,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9962999820709229,"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-state-information","display_name":"Channel state information","score":0.8383960723876953},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.803455114364624},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.6986032128334045},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5574862957000732},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.5485650897026062},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48793336749076843},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4741972088813782},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4022391736507416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40057188272476196},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36520063877105713},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.26388126611709595},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1373218297958374}],"concepts":[{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.8383960723876953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.803455114364624},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.6986032128334045},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5574862957000732},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.5485650897026062},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48793336749076843},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4741972088813782},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4022391736507416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40057188272476196},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36520063877105713},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.26388126611709595},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1373218297958374},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lwc.2024.3407813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2024.3407813","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"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 Wireless Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2293567989","https://openalex.org/W2884366600","https://openalex.org/W2886124254","https://openalex.org/W2901240584","https://openalex.org/W2963145597","https://openalex.org/W2963420686","https://openalex.org/W2982624119","https://openalex.org/W3003689553","https://openalex.org/W3199506096","https://openalex.org/W4205806546","https://openalex.org/W4290996376","https://openalex.org/W4312050602"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2059045613","https://openalex.org/W884630482","https://openalex.org/W2025723618","https://openalex.org/W2552025594","https://openalex.org/W4211013851"],"abstract_inverted_index":{"In":[0],"5G":[1],"communications,":[2],"the":[3,14,44,61,77,102],"precision":[4],"of":[5,109],"Channel":[6],"State":[7],"Information":[8],"(CSI)":[9],"feedback":[10,37,53],"is":[11],"vital,":[12],"and":[13,105,114],"massive":[15],"Multiple-Input":[16],"Multiple-Output":[17],"(MIMO)":[18],"systems":[19],"rely":[20],"heavily":[21],"on":[22,94],"this":[23,57],"for":[24,52],"optimal":[25],"performance.":[26],"While":[27],"eigenvector-based":[28],"methods":[29],"using":[30],"Deep":[31],"Learning":[32],"(DL)":[33],"have":[34],"innovated":[35],"CSI":[36,48,82],"mechanisms,":[38],"they":[39],"do":[40],"not":[41],"fully":[42],"exploit":[43],"intrinsic":[45],"correlations":[46,79],"within":[47],"that":[49,74],"are":[50,89],"instrumental":[51],"optimization.":[54],"To":[55],"bridge":[56],"gap,":[58],"we":[59],"propose":[60],"Data":[62],"ARrangEment":[63],"Neural":[64,69],"Network":[65,70],"(DARENet),":[66],"a":[67],"Convolutional":[68],"(CNN)":[71],"based":[72],"framework":[73],"effectively":[75],"utilizes":[76],"inherent":[78],"present":[80],"in":[81,107],"eigenvectors":[83],"with":[84],"cross-polarized":[85],"antennas.":[86],"DARENet\u2019s":[87],"capabilities":[88],"validated":[90],"through":[91],"rigorous":[92],"testing":[93],"5":[95],"public":[96],"datasets,":[97],"where":[98],"it":[99],"consistently":[100],"outperforms":[101],"established":[103],"EVCsiNet":[104],"PolarDenseNet":[106],"terms":[108],"recovery":[110],"performance,":[111],"computational":[112],"efficiency,":[113],"model":[115],"complexity.":[116]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}