{"id":"https://openalex.org/W4414538767","doi":"https://doi.org/10.1109/icc52391.2025.11161293","title":"Physics-Inspired Distributed Radio Map Estimation","display_name":"Physics-Inspired Distributed Radio Map Estimation","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414538767","doi":"https://doi.org/10.1109/icc52391.2025.11161293"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161293","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030530989","display_name":"Dong Yang","orcid":"https://orcid.org/0000-0002-2695-0499"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Yang","raw_affiliation_strings":["Georgia State University,Department of Computer Science,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia State University,Department of Computer Science,Atlanta,GA,USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372101","display_name":"Yue Wang","orcid":"https://orcid.org/0000-0003-0901-7610"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Georgia State University,Department of Computer Science,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia State University,Department of Computer Science,Atlanta,GA,USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100747791","display_name":"Songyang Zhang","orcid":"https://orcid.org/0000-0002-2895-5728"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Songyang Zhang","raw_affiliation_strings":["University of Louisiana at Lafayette,LA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Louisiana at Lafayette,LA,USA","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102441686","display_name":"Yingshu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingshu Li","raw_affiliation_strings":["Georgia State University,Department of Computer Science,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia State University,Department of Computer Science,Atlanta,GA,USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072627238","display_name":"Zhipeng Cai","orcid":"https://orcid.org/0000-0001-6017-975X"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhipeng Cai","raw_affiliation_strings":["Georgia State University,Department of Computer Science,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia State University,Department of Computer Science,Atlanta,GA,USA","institution_ids":["https://openalex.org/I181565077"]}]}],"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":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1025","last_page":"1030"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.8593999743461609,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.8593999743461609,"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/autoencoder","display_name":"Autoencoder","score":0.8810999989509583},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6751999855041504},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5587000250816345},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5024999976158142},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.48579999804496765},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"Distributed learning","score":0.43299999833106995},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.38280001282691956},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3718999922275543},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.3555999994277954}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8810999989509583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7813000082969666},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6751999855041504},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5587000250816345},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5044000148773193},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5024999976158142},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.48579999804496765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43720000982284546},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.43299999833106995},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.38280001282691956},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3718999922275543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3630000054836273},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3555999994277954},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3515999913215637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3474999964237213},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3450999855995178},{"id":"https://openalex.org/C2781234732","wikidata":"https://www.wikidata.org/wiki/Q943505","display_name":"Fusion center","level":4,"score":0.33869999647140503},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.31299999356269836},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.28999999165534973},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C182448111","wikidata":"https://www.wikidata.org/wiki/Q7281197","display_name":"Radio resource management","level":4,"score":0.2870999872684479},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C202311505","wikidata":"https://www.wikidata.org/wiki/Q1474701","display_name":"Radio propagation","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.27790001034736633},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C508800617","wikidata":"https://www.wikidata.org/wiki/Q29643","display_name":"Wi-Fi","level":4,"score":0.2694999873638153},{"id":"https://openalex.org/C76843793","wikidata":"https://www.wikidata.org/wiki/Q1474701","display_name":"Radio propagation model","level":3,"score":0.2671999931335449},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.2549999952316284},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11161293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161293","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1768046184","display_name":null,"funder_award_id":"2146497,2231209,2244219,2315596,2413622,2425811","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1498305593","https://openalex.org/W2005614662","https://openalex.org/W2006554558","https://openalex.org/W2042696029","https://openalex.org/W2056168581","https://openalex.org/W2562456622","https://openalex.org/W2883649322","https://openalex.org/W3108838069","https://openalex.org/W3131967102","https://openalex.org/W3173269149","https://openalex.org/W3212618958","https://openalex.org/W4237914606","https://openalex.org/W4298352247","https://openalex.org/W4386090251","https://openalex.org/W4387430923","https://openalex.org/W4391069941","https://openalex.org/W4391621154","https://openalex.org/W4394966940","https://openalex.org/W4396598347","https://openalex.org/W4399728347","https://openalex.org/W4401507886","https://openalex.org/W4406266345","https://openalex.org/W4406267631"],"related_works":[],"abstract_inverted_index":{"To":[0,114,152],"gain":[1],"panoramic":[2],"awareness":[3],"of":[4,41,95,105,148],"spectrum":[5,32],"coverage":[6],"in":[7,38,76,84,111,128,211,224],"complex":[8],"wireless":[9],"environments,":[10],"data-driven":[11],"learning":[12,26,68,160,197],"approaches":[13],"have":[14],"recently":[15],"been":[16],"introduced":[17],"for":[18,125],"radio":[19,149,187],"map":[20],"estimation":[21],"(RME).":[22],"While":[23],"existing":[24],"deep":[25,167],"based":[27],"methods":[28],"conduct":[29],"RME":[30,77,98,123,140,166],"given":[31],"measurements":[33],"gathered":[34],"from":[35,206],"dispersed":[36],"sensors":[37],"the":[39,46,93,96,103,145,164,182,198,207,222],"region":[40],"interest,":[42],"they":[43],"rely":[44],"on":[45,59,186,196],"centralized":[47],"data":[48,60,71],"collected":[49],"at":[50],"a":[51,120,137,157,191],"fusion":[52],"center,":[53],"which":[54],"unfortunately":[55],"raises":[56],"critical":[57],"concerns":[58],"privacy":[61],"leakages":[62],"and":[63,73],"high":[64],"communication":[65,74],"overloads.":[66],"Federated":[67],"(FL)":[69],"enhances":[70],"security":[72],"efficiency":[75],"by":[78,102,143,202],"allowing":[79],"multiple":[80],"clients":[81,109,179],"to":[82,135,180],"collaborate":[83],"model":[85,168],"training":[86],"without":[87],"directly":[88],"sharing":[89],"local":[90,203,212],"data.":[91],"However,":[92],"performance":[94],"FL-based":[97],"might":[99],"be":[100],"hindered":[101],"problem":[104],"task":[106],"heterogeneity":[107],"across":[108],"located":[110],"different":[112],"environments.":[113],"fill":[115],"this":[116,129],"gap,":[117],"we":[118,155],"propose":[119],"physicsinspired":[121],"distributed":[122,139,159],"solution":[124],"heterogeneous":[126],"settings":[127],"paper.":[130],"The":[131],"key":[132],"idea":[133],"is":[134,176],"develop":[136],"novel":[138],"framework":[141],"empowered":[142],"leveraging":[144],"domain":[146],"knowledge":[147],"propagation":[150,188],"models.":[151],"do":[153],"so,":[154],"design":[156],"new":[158],"approach":[161],"that":[162,217],"splits":[163],"entire":[165],"into":[169],"two":[170],"modules.":[171],"A":[172],"global":[173],"autoencoder":[174,193],"module":[175,194],"shared":[177],"among":[178],"capture":[181],"common":[183],"pathloss":[184],"influence":[185],"patterns,":[189],"while":[190],"client-specific":[192],"focuses":[195],"individual":[199],"features":[200],"produced":[201],"shadowing":[204],"effects":[205],"unique":[208],"building":[209],"distributions":[210],"environment.":[213],"Simulation":[214],"results":[215],"show":[216],"our":[218],"proposed":[219],"method":[220],"outperforms":[221],"benchmarks":[223],"achieving":[225],"higher":[226],"performance.":[227]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
