{"id":"https://openalex.org/W7165878493","doi":"https://doi.org/10.48550/arxiv.2606.25101","title":"Wideband Near-Field Channel Estimation Under Hybrid Compression: Cross-Subcarrier KL Covariance Fitting With OFDM Fresnel Model","display_name":"Wideband Near-Field Channel Estimation Under Hybrid Compression: Cross-Subcarrier KL Covariance Fitting With OFDM Fresnel Model","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7165878493","doi":"https://doi.org/10.48550/arxiv.2606.25101"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.25101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25101","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":null,"license_id":null,"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.2606.25101","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139356709","display_name":"R\u0131fat Volkan \u015eenyuva","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"\u015eenyuva, R\u0131fat Volkan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5139356709"],"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.5593000054359436,"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"}},"topics":[{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.5593000054359436,"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"}},{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.12690000236034393,"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":0.05009999871253967,"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/wideband","display_name":"Wideband","score":0.8115000128746033},{"id":"https://openalex.org/keywords/narrowband","display_name":"Narrowband","score":0.7401999831199646},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.6254000067710876},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5831000208854675},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5720000267028809},{"id":"https://openalex.org/keywords/orthogonal-frequency-division-multiplexing","display_name":"Orthogonal frequency-division multiplexing","score":0.4918000102043152},{"id":"https://openalex.org/keywords/cram\u00e9r\u2013rao-bound","display_name":"Cram\u00e9r\u2013Rao bound","score":0.40880000591278076},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.40540000796318054}],"concepts":[{"id":"https://openalex.org/C2780202535","wikidata":"https://www.wikidata.org/wiki/Q4524457","display_name":"Wideband","level":2,"score":0.8115000128746033},{"id":"https://openalex.org/C2776096036","wikidata":"https://www.wikidata.org/wiki/Q1140483","display_name":"Narrowband","level":2,"score":0.7401999831199646},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.6254000067710876},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5831000208854675},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5720000267028809},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5386999845504761},{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.4918000102043152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41850000619888306},{"id":"https://openalex.org/C4978587","wikidata":"https://www.wikidata.org/wiki/Q1138810","display_name":"Cram\u00e9r\u2013Rao bound","level":3,"score":0.40880000591278076},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36239999532699585},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3066999912261963},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2994999885559082},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.26969999074935913},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.2653000056743622},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C200292535","wikidata":"https://www.wikidata.org/wiki/Q1455719","display_name":"Fresnel zone","level":3,"score":0.26330000162124634},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.25949999690055847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.25101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25101","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.25101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25101","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8518614172935486,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,73,116],"consider":[1],"wideband":[2,120],"channel":[3,50],"estimation":[4],"for":[5,130],"extremely":[6],"large-scale":[7],"multiple-input":[8],"multiple-output":[9],"(XL-MIMO)":[10],"arrays":[11],"under":[12],"hybrid":[13,132],"analog-digital":[14],"compression,":[15],"in":[16],"which":[17,81],"a":[18,34,98,110,148,155,180,188,199,216],"uniform":[19],"linear":[20],"array":[21],"(ULA)":[22],"is":[23,241],"observed":[24],"through":[25],"far":[26],"fewer":[27],"radio-frequency":[28],"(RF)":[29],"chains":[30],"than":[31],"antennas.":[32],"At":[33],"carrier":[35],"frequency":[36],"of":[37,151,158,184,201,219,226],"28":[38],"GHz":[39],"with":[40],"bandwidths":[41],"reaching":[42],"several":[43],"hundred":[44],"MHz,":[45],"the":[46,53,60,64,75,89,119,126,136,144,174,204,222,233,238,244],"standard":[47],"narrowband":[48,70,145],"polar-domain":[49],"model":[51,102],"fails:":[52],"near-field":[54],"Fresnel":[55,100],"curvature":[56],"becomes":[57],"subcarrier-dependent,":[58],"and":[59,85,139,154,171,210],"compressed":[61,90],"observation":[62],"destroys":[63],"per-subcarrier":[65],"spatial":[66],"covariance":[67,101],"structure":[68],"that":[69],"methods":[71],"exploit.":[72],"propose":[74],"Wideband":[76],"Cross-subcarrier":[77],"Kullback--Leibler":[78,112],"(WB-CL-KL)":[79],"estimator,":[80],"jointly":[82],"estimates":[83],"angle":[84],"range":[86,181],"directly":[87],"from":[88,135],"sample":[91],"covariance,":[92],"without":[93],"full-array":[94],"reconstruction,":[95],"by":[96],"fitting":[97],"structured":[99],"across":[103],"orthogonal":[104],"frequency-division":[105],"multiplexing":[106],"(OFDM)":[107],"subcarriers":[108],"via":[109],"cross-subcarrier":[111],"(KL)":[113],"divergence":[114],"criterion.":[115],"also":[117],"derive":[118],"compressed-domain":[121,239],"Cram\u00e9r--Rao":[122],"bound":[123,129,146,191,217,240],"(CRB)":[124],"--":[125,134],"performance":[127],"lower":[128],"this":[131],"architecture":[133],"Slepian--Bangs":[137],"formula,":[138],"decompose":[140],"its":[141],"gain":[142],"over":[143],"into":[147],"data-diversity":[149],"component":[150,157],"+27.093":[152],"dB":[153,163],"geometric-diversity":[156],"+0.701":[159],"dB,":[160,198,228],"totalling":[161],"+27.793":[162],"at":[164,192,221,232,243],"B":[165],"=":[166,196],"400":[167],"MHz":[168],"(Propositions":[169],"1":[170],"2).":[172],"In":[173],"single-path":[175],"line-of-sight":[176],"regime,":[177],"WB-CL-KL":[178],"attains":[179],"root-mean-square":[182],"error":[183],"19.8":[185],"mm":[186,190],"against":[187],"19.9":[189],"signal-to-noise":[193],"ratio":[194,200,218],"(SNR)":[195],"10":[197],"0.996.":[202],"Under":[203],"3GPP":[205],"Urban":[206],"Micro":[207],"(UMi)":[208],"path-loss":[209],"shadow-fading":[211],"SNR":[212,225],"distribution,":[213],"it":[214],"achieves":[215],"0.959":[220],"median":[223],"deployment":[224,235],"9.6":[227],"indicating":[229],"near-CRB":[230],"operation":[231],"representative":[234],"point,":[236],"where":[237],"evaluated":[242],"scene-median":[245],"geometry.":[246]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-26T00:00:00"}
