{"id":"https://openalex.org/W4408325628","doi":"https://doi.org/10.1109/globecom52923.2024.10901360","title":"Joint Spectrum Cartography and Prediction via Tensor-Structural Self-Supervised Regularization","display_name":"Joint Spectrum Cartography and Prediction via Tensor-Structural Self-Supervised Regularization","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4408325628","doi":"https://doi.org/10.1109/globecom52923.2024.10901360"},"language":"en","primary_location":{"id":"doi:10.1109/globecom52923.2024.10901360","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","raw_type":"proceedings-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/A5058044634","display_name":"Xiaonan Chen","orcid":"https://orcid.org/0000-0002-8335-778X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaonan Chen","raw_affiliation_strings":["Univ. Electron. Sci. Technol,National Key Lab. Wirel. Commun.,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Electron. Sci. Technol,National Key Lab. Wirel. Commun.,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384675","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-0322-0063"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Univ. Electron. Sci. Technol,National Key Lab. Wirel. Commun.,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Electron. Sci. Technol,National Key Lab. Wirel. Commun.,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066720367","display_name":"Qingyang Huang","orcid":"https://orcid.org/0000-0001-8274-4588"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyang Huang","raw_affiliation_strings":["Univ. Electron. Sci. Technol,National Key Lab. Wirel. Commun.,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Electron. Sci. Technol,National Key Lab. Wirel. Commun.,China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27048995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2773","last_page":"2778"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9764000177383423,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9463000297546387,"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/regularization","display_name":"Regularization (linguistics)","score":0.6742777824401855},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5360199809074402},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5094714760780334},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48215433955192566},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4384867548942566},{"id":"https://openalex.org/keywords/spectrum","display_name":"Spectrum (functional analysis)","score":0.41916725039482117},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34004226326942444},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33186620473861694},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20348656177520752},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.16838034987449646},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1340067982673645},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.08593639731407166}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6742777824401855},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5360199809074402},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5094714760780334},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48215433955192566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4384867548942566},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.41916725039482117},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34004226326942444},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33186620473861694},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20348656177520752},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.16838034987449646},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1340067982673645},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.08593639731407166},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom52923.2024.10901360","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.5299999713897705,"display_name":"Climate action"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327471","display_name":"China Aerospace Science and Technology Corporation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2091484400","https://openalex.org/W2127856853","https://openalex.org/W2157879939","https://openalex.org/W2227958069","https://openalex.org/W2552259797","https://openalex.org/W2791154158","https://openalex.org/W2883649322","https://openalex.org/W2988379071","https://openalex.org/W2991033093","https://openalex.org/W3159843227","https://openalex.org/W3170639163","https://openalex.org/W4200379301","https://openalex.org/W4286539639","https://openalex.org/W4323796443","https://openalex.org/W4327662624","https://openalex.org/W4389160161"],"related_works":["https://openalex.org/W1996130883","https://openalex.org/W2748574964","https://openalex.org/W2888483922","https://openalex.org/W4396737233","https://openalex.org/W2367747139","https://openalex.org/W4391102217","https://openalex.org/W2566187525","https://openalex.org/W2566334511","https://openalex.org/W2367150592","https://openalex.org/W4254199101"],"abstract_inverted_index":{"Spectrum":[0],"cartography":[1,58],"(SC)":[2],"and":[3,27,44,59,106,119,141],"spectrum":[4,12,57],"prediction":[5,60],"(SP)":[6],"are":[7,39],"homologous":[8],"tasks":[9,38,67],"in":[10,47,68],"the":[11,17,28,36,65,76,92,124],"sensing":[13],"(SS)":[14],"realm,":[15],"where":[16,83],"former":[18],"reconstructs":[19],"multi-domain":[20],"radio":[21,32,81],"maps":[22],"from":[23],"sparse":[24],"historical":[25],"samples,":[26],"latter":[29],"predicts":[30],"upcoming":[31],"frequency":[33],"status.":[34],"Nonetheless,":[35],"two":[37,66],"oftentimes":[40],"considered":[41],"mutually":[42],"exclusive":[43],"tackled":[45],"separately":[46],"existing":[48],"literature.":[49],"This":[50],"work":[51],"artfully":[52],"puts":[53],"forth":[54],"a":[55,69,86,98,102,145],"joint":[56],"(JSCP)":[61],"framework":[62],"that":[63,133],"addresses":[64],"unified":[70],"way.":[71],"Our":[72],"idea":[73],"rests":[74],"upon":[75],"tensor":[77,94],"(space-frequency-time)":[78],"structure":[79],"of":[80,127,147],"maps,":[82],"we":[84],"incorporate":[85],"latent":[87],"temporal":[88],"regression":[89,99],"system":[90,100],"into":[91],"relative":[93],"decomposition":[95],"factor.":[96],"Such":[97],"enjoys":[101],"self-supervised":[103],"optimization":[104],"flavor,":[105],"is":[107],"utilized":[108],"for":[109],"enhancing":[110],"collaborative":[111],"SC/SP":[112],"performances.":[113],"We":[114],"propose":[115],"both":[116],"theoretical":[117],"guarantee":[118],"effective":[120],"algorithm":[121],"to":[122],"solve":[123],"resultant":[125],"problems":[126],"JSCP":[128],"framework.":[129],"Simulation":[130],"results":[131],"verify":[132],"our":[134],"approaches":[135],"have":[136],"more":[137],"promising":[138],"estimation":[139],"accuracy":[140],"generalizability":[142],"compared":[143],"with":[144],"variety":[146],"baselines.":[148]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
