{"id":"https://openalex.org/W4414539679","doi":"https://doi.org/10.1109/icc52391.2025.11161317","title":"One-Shot Near-Field Localization with Ai-Optimized Hybrid Beamformer Design","display_name":"One-Shot Near-Field Localization with Ai-Optimized Hybrid Beamformer Design","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414539679","doi":"https://doi.org/10.1109/icc52391.2025.11161317"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161317","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161317","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/11585/1044968","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078600078","display_name":"Mattia Fabiani","orcid":"https://orcid.org/0009-0001-4114-5148"},"institutions":[{"id":"https://openalex.org/I4210098188","display_name":"Laboratori Guglielmo Marconi (Italy)","ror":"https://ror.org/01r3vad87","country_code":"IT","type":"company","lineage":["https://openalex.org/I4210098188"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mattia Fabiani","raw_affiliation_strings":["University of Bologna,Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”,Bologna,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bologna,Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”,Bologna,Italy","institution_ids":["https://openalex.org/I4210098188"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064176463","display_name":"Davide Dardari","orcid":"https://orcid.org/0000-0002-5994-1310"},"institutions":[{"id":"https://openalex.org/I4210098188","display_name":"Laboratori Guglielmo Marconi (Italy)","ror":"https://ror.org/01r3vad87","country_code":"IT","type":"company","lineage":["https://openalex.org/I4210098188"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Davide Dardari","raw_affiliation_strings":["University of Bologna,Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”,Bologna,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bologna,Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”,Bologna,Italy","institution_ids":["https://openalex.org/I4210098188"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031155839","display_name":"Antonio A. D\u2019Amico","orcid":"https://orcid.org/0000-0002-4017-7439"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Antonio A. D'Amico","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063635284","display_name":"Luca Sanguinetti","orcid":"https://orcid.org/0000-0002-2577-4091"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Sanguinetti","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy","institution_ids":["https://openalex.org/I108290504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2509","last_page":"2513"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9979000091552734,"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/T11946","display_name":"Antenna Design and Optimization","score":0.9943000078201294,"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/T11851","display_name":"Electromagnetic Compatibility and Measurements","score":0.9929999709129333,"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/robustness","display_name":"Robustness (evolution)","score":0.6279000043869019},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5530999898910522},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.503000020980835},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4474000036716461},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.44679999351501465},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4325000047683716},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4189999997615814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7260000109672546},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6279000043869019},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5530999898910522},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.503000020980835},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4474000036716461},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.44679999351501465},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4307999908924103},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4189999997615814},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3296000063419342},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3098999857902527},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.2831999957561493},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2831000089645386},{"id":"https://openalex.org/C2779990667","wikidata":"https://www.wikidata.org/wiki/Q5953266","display_name":"Hybrid neural network","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25949999690055847}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icc52391.2025.11161317","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161317","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"},{"id":"pmh:oai:cris.unibo.it:11585/1044968","is_oa":true,"landing_page_url":"https://hdl.handle.net/11585/1044968","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:cris.unibo.it:11585/1044968","is_oa":true,"landing_page_url":"https://hdl.handle.net/11585/1044968","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G41775389","display_name":null,"funder_award_id":"HORIZON-JU-SNS-2022","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8667744673","display_name":"THz Industrial Mesh Networks in Smart Sensing and Propagation Environments","funder_award_id":"101096307","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2909191390","https://openalex.org/W2965065251","https://openalex.org/W2984477042","https://openalex.org/W3147854096","https://openalex.org/W4205909476","https://openalex.org/W4226370247","https://openalex.org/W4294310096","https://openalex.org/W4296208618","https://openalex.org/W4309270041","https://openalex.org/W4385885073","https://openalex.org/W4392026394","https://openalex.org/W4400111516"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"a":[3,13,69,94,120],"learning-based":[4],"approach":[5],"to":[6,35,50],"the":[7,32,36,44,62,78,89,98,101,108,112,116,129],"near-field":[8,56,91],"source":[9],"localization":[10,57],"problem":[11],"adopting":[12],"hybrid":[14,53],"analog-digital":[15,26],"beamformer":[16,80,113],"in":[17,31,61,93,137],"an":[18],"extremely":[19],"large-scale":[20],"multipleinput":[21],"multiple-output":[22],"(XL-MIMO)":[23],"system.":[24],"Hybrid":[25],"architectures":[27],"gained":[28],"significant":[29],"attention":[30],"literature":[33],"due":[34],"limited":[37],"number":[38],"of":[39,46,128],"radio-frequency":[40],"(RF)":[41],"chains.":[42],"However,":[43],"investigation":[45],"effective":[47],"techniques":[48],"tailored":[49],"partially":[51],"connected":[52],"beamformers":[54],"for":[55,111],"is":[58,103,145],"still":[59],"missing":[60],"literature.":[63],"To":[64],"this":[65],"end,":[66],"we":[67],"leverage":[68],"Convolutional":[70],"Neural":[71],"Network":[72],"(CNN)-based":[73],"model":[74,102],"to:":[75],"(i)":[76],"perform":[77],"analog":[79],"design":[81],"with":[82],"proper":[83],"training":[84],"constraints;":[85],"and":[86,115,135,147],"(ii)":[87],"estimate":[88],"single-user":[90],"position":[92],"single":[95],"snapshot.":[96],"In":[97,141],"inference":[99],"stage,":[100],"divided":[104],"into":[105],"two":[106],"parts:":[107],"first":[109],"accounts":[110],"design,":[114],"second":[117],"acts":[118],"as":[119],"localizing":[121],"function.":[122],"Simulation":[123],"results":[124],"demonstrate":[125],"superior":[126],"performance":[127],"proposed":[130],"method":[131],"over":[132],"existing":[133],"solutions":[134],"robustness":[136],"multipath":[138],"propagation":[139],"conditions.":[140],"addition,":[142],"our":[143],"network":[144],"scalable":[146],"requires":[148],"fewer":[149],"RF":[150],"chains":[151],"than":[152],"fullyconnected":[153],"architectures.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}