{"id":"https://openalex.org/W4408352624","doi":"https://doi.org/10.1109/icassp49660.2025.10890350","title":"Integrated Interpolation and Matrix Completion for Radio Map Estimation: A Convex Optimization Approach","display_name":"Integrated Interpolation and Matrix Completion for Radio Map Estimation: A Convex Optimization Approach","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408352624","doi":"https://doi.org/10.1109/icassp49660.2025.10890350"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10890350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5108393831","display_name":"Hongcheng Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongcheng Dong","raw_affiliation_strings":["The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101549750","display_name":"Wenqiang Pu","orcid":"https://orcid.org/0000-0003-1683-6948"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqiang Pu","raw_affiliation_strings":["The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103131918","display_name":"Rui Zhou","orcid":"https://orcid.org/0000-0002-9463-0390"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhou","raw_affiliation_strings":["The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015075381","display_name":"Xiao Fu","orcid":"https://orcid.org/0000-0003-4847-9586"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Fu","raw_affiliation_strings":["Oregon State University,School of Electrical Engineering and Computer Science,Corvallis,OR,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Oregon State University,School of Electrical Engineering and Computer Science,Corvallis,OR,USA","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100696174","display_name":"Feng Yin","orcid":"https://orcid.org/0000-0001-5754-9246"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yin","raw_affiliation_strings":["The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.4653,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92243647,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11946","display_name":"Antenna Design and Optimization","score":0.996399998664856,"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/T11946","display_name":"Antenna Design and Optimization","score":0.996399998664856,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9948999881744385,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9925000071525574,"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/matrix-completion","display_name":"Matrix completion","score":0.8161749839782715},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6757262945175171},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5595265030860901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5486019253730774},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5076810121536255},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.457713782787323},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.43718820810317993},{"id":"https://openalex.org/keywords/matrix-algebra","display_name":"Matrix algebra","score":0.4127694070339203},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35225164890289307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32263749837875366},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.24104824662208557},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06400752067565918}],"concepts":[{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.8161749839782715},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6757262945175171},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5595265030860901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5486019253730774},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5076810121536255},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.457713782787323},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.43718820810317993},{"id":"https://openalex.org/C2988995629","wikidata":"https://www.wikidata.org/wiki/Q2915729","display_name":"Matrix algebra","level":3,"score":0.4127694070339203},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35225164890289307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32263749837875366},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.24104824662208557},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06400752067565918},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10890350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320330944","display_name":"Nature","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1969698720","https://openalex.org/W2040895929","https://openalex.org/W2048695508","https://openalex.org/W2095143852","https://openalex.org/W2126663866","https://openalex.org/W2315686272","https://openalex.org/W2611328865","https://openalex.org/W2787894218","https://openalex.org/W2947146353","https://openalex.org/W2991033093","https://openalex.org/W3081154744","https://openalex.org/W3118241766","https://openalex.org/W3131967102","https://openalex.org/W3159843227","https://openalex.org/W3208027747","https://openalex.org/W4221160010","https://openalex.org/W4291910407","https://openalex.org/W4296079337","https://openalex.org/W4312622783","https://openalex.org/W4313007552","https://openalex.org/W4389160161","https://openalex.org/W4401536878","https://openalex.org/W6682042988","https://openalex.org/W6740036592","https://openalex.org/W6847381358","https://openalex.org/W6863608765","https://openalex.org/W6907655010"],"related_works":["https://openalex.org/W2994409951","https://openalex.org/W4293326902","https://openalex.org/W2604249670","https://openalex.org/W2953063457","https://openalex.org/W3115944395","https://openalex.org/W2266965707","https://openalex.org/W2082020694","https://openalex.org/W2912837894","https://openalex.org/W1980119287","https://openalex.org/W4401717669"],"abstract_inverted_index":{"Radio":[0],"map":[1],"estimation":[2],"(RME)":[3],"is":[4],"crucial":[5],"for":[6,64],"effective":[7],"planning":[8],"and":[9,49,113],"optimization":[10,62],"of":[11,47,99],"wireless":[12],"networks.":[13],"Traditional":[14],"approaches":[15,39],"such":[16],"as":[17,78],"interpolation":[18,69],"excel":[19],"at":[20],"capturing":[21],"local":[22],"smoothness":[23],"in":[24,127],"densely":[25],"populated":[26],"data":[27],"but":[28,43],"struggle":[29],"with":[30,70],"sparse":[31],"or":[32],"irregular":[33],"data.":[34],"Conversely,":[35],"matrix":[36],"completion":[37],"(MC)":[38],"utilize":[40],"global":[41],"structures":[42],"require":[44],"huge":[45],"number":[46],"samples":[48],"may":[50],"produce":[51],"non-smooth":[52],"estimates.":[53],"To":[54],"integrate":[55],"these":[56],"strengths,":[57],"we":[58,88],"propose":[59],"a":[60,79,91],"convex":[61],"approach":[63,73],"RME":[65,76],"(IIMC-RME)":[66],"that":[67,118],"merges":[68],"MC.":[71],"This":[72],"formulates":[74],"the":[75,95,105],"task":[77],"low-rank":[80],"MC":[81],"problem":[82],"constrained":[83],"by":[84],"interpolated":[85],"results.":[86],"Additionally,":[87],"have":[89,116],"developed":[90],"convergent":[92],"algorithm":[93],"utilizing":[94],"alternating":[96],"direction":[97],"method":[98],"multipliers":[100],"(ADMM)":[101],"to":[102],"efficiently":[103],"solve":[104],"IIMC-RME":[106,119],"problem.":[107],"Experimental":[108],"evaluations":[109],"on":[110],"both":[111],"synthetic":[112],"real-world":[114],"datasets":[115],"shown":[117],"surpasses":[120],"existing":[121],"approaches,":[122],"thereby":[123],"achieving":[124],"superior":[125],"accuracy":[126],"RME.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
