{"id":"https://openalex.org/W4401694067","doi":"https://doi.org/10.1109/dyspan60163.2024.10632773","title":"Geo2SigMap: High-Fidelity RF Signal Mapping Using Geographic Databases","display_name":"Geo2SigMap: High-Fidelity RF Signal Mapping Using Geographic Databases","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401694067","doi":"https://doi.org/10.1109/dyspan60163.2024.10632773"},"language":"en","primary_location":{"id":"doi:10.1109/dyspan60163.2024.10632773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dyspan60163.2024.10632773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","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/A5101829925","display_name":"Yiming Li","orcid":"https://orcid.org/0000-0003-1898-2156"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yiming Li","raw_affiliation_strings":["Duke University,Department of Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Duke University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058083490","display_name":"Zeyu Li","orcid":"https://orcid.org/0000-0001-5927-6560"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zeyu Li","raw_affiliation_strings":["Duke University,Department of Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Duke University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062987872","display_name":"Zhihui Gao","orcid":"https://orcid.org/0000-0001-6123-7165"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhihui Gao","raw_affiliation_strings":["Duke University,Department of Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Duke University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034818470","display_name":"Tingjun Chen","orcid":"https://orcid.org/0000-0002-5717-5755"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tingjun Chen","raw_affiliation_strings":["Duke University,Department of Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Duke University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101829925"],"corresponding_institution_ids":["https://openalex.org/I170897317"],"apc_list":null,"apc_paid":null,"fwci":4.1538,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.94796954,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"277","last_page":"285"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.8971999883651733,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.8971999883651733,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11234","display_name":"Precipitation Measurement and Analysis","score":0.7674000263214111,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.651997983455658},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.5285467505455017},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.4856392443180084},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.44915762543678284},{"id":"https://openalex.org/keywords/radio-frequency","display_name":"Radio frequency","score":0.41624733805656433},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16472968459129333},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1001182496547699},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.07374227046966553}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.651997983455658},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.5285467505455017},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.4856392443180084},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.44915762543678284},{"id":"https://openalex.org/C74064498","wikidata":"https://www.wikidata.org/wiki/Q3396184","display_name":"Radio frequency","level":2,"score":0.41624733805656433},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16472968459129333},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1001182496547699},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.07374227046966553}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dyspan60163.2024.10632773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dyspan60163.2024.10632773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4313443006","https://openalex.org/W2945374968","https://openalex.org/W4385452045","https://openalex.org/W4293777179","https://openalex.org/W2164070813","https://openalex.org/W2135608140","https://openalex.org/W2895525995","https://openalex.org/W4224231624","https://openalex.org/W2332512904","https://openalex.org/W2319626700"],"abstract_inverted_index":{"Radio":[0],"frequency":[1],"(RF)":[2],"signal":[3,15,34,84,96,147,206,273],"mapping,":[4],"which":[5,45,57,86,194],"is":[6,22,195],"the":[7,13,62,106,125,131,175,218,249,271,278],"process":[8],"of":[9,108,178,220,230,266,285],"analyzing":[10],"and":[11,17,28,144,170,183,200,211],"predicting":[12,270],"RF":[14,33,83,95,146,205],"strength":[16],"distribution":[18],"across":[19],"specific":[20],"areas,":[21],"crucial":[23],"for":[24,61,81,112,142,269],"cellular":[25,241],"network":[26],"planning":[27],"deployment.":[29],"Traditional":[30],"approaches":[31],"to":[32,93,128,202,240,289],"mapping":[35,97,148],"rely":[36,120],"on":[37,42,90,121,197],"statistical":[38],"models":[39,88],"constructed":[40],"based":[41],"measurement":[43,213,225],"data,":[44],"offer":[46],"low":[47],"complexity":[48],"but":[49,65],"often":[50,104],"lack":[51],"accuracy,":[52],"or":[53,119],"ray":[54,117,184],"tracing":[55,185],"tools,":[56],"provide":[58],"enhanced":[59],"precision":[60],"target":[63],"area":[64],"suffer":[66],"from":[67,124,243],"increased":[68],"computational":[69],"complexity.":[70],"Recently,":[71],"machine":[72],"learning":[73],"(ML)":[74],"has":[75],"emerged":[76],"as":[77],"a":[78,190,223],"data-driven":[79],"method":[80],"modeling":[82],"propagation,":[85],"leverages":[87],"trained":[89],"synthetic":[91,114,198],"datasets":[92,115,199],"perform":[94],"in":[98,248],"\u201cunseen\u201d":[99],"areas.":[100],"However,":[101],"such":[102],"methods":[103],"require":[105],"use":[107],"advanced":[109],"proprietary":[110],"software":[111],"creating":[113],"(e.g.,":[116],"tracing),":[118,173],"measurements":[122],"collected":[123],"unseen":[126],"areas":[127],"effectively":[129],"train":[130],"models.":[132,186],"In":[133],"this":[134],"paper,":[135],"we":[136,153,188,216],"present":[137],"Geo2SigMap,":[138],"an":[139,155,262,281],"ML-based":[140],"frame-work":[141,157],"efficient":[143,176],"high-fidelity":[145],"using":[149],"geographic":[150],"databases.":[151],"First,":[152],"develop":[154],"automated":[156],"that":[158,259],"seamlessly":[159],"integrates":[160],"three":[161,228],"open-source":[162],"tools:":[163],"Open-StreetMap":[164],"(geographic":[165],"databases),":[166],"Blender":[167],"(computer":[168],"graphics),":[169],"Sionna":[171],"(ray":[172],"enabling":[174],"generation":[177],"large-scale":[179],"3D":[180],"building":[181],"maps":[182],"Second,":[187],"propose":[189],"cascaded":[191],"U-Net":[192],"model,":[193],"pre-trained":[196],"employed":[201],"generate":[203],"detailed":[204],"maps,":[207],"leveraging":[208],"environmental":[209],"information":[210,242],"sparse":[212],"data.":[214],"Finally,":[215],"evaluate":[217],"performance":[219],"Geo2SigMap":[221,260],"via":[222],"real-world":[224],"campaign,":[226],"where":[227],"types":[229],"user":[231],"equipment":[232],"(UE)":[233],"collect":[234],"over":[235],"45,000":[236],"data":[237],"points":[238],"related":[239],"six":[244],"LTE":[245],"cells":[246],"operating":[247],"citizens":[250],"broadband":[251],"radio":[252],"service":[253],"(CBRS)":[254],"band.":[255],"Our":[256],"results":[257],"show":[258],"achieves":[261],"average":[263,282],"root-mean-square-error":[264],"(RMSE)":[265],"6.04":[267],"dB":[268,287],"reference":[272],"received":[274],"power":[275],"(RSRP)":[276],"at":[277],"UE,":[279],"representing":[280],"RMSE":[283],"improvement":[284],"3.59":[286],"compared":[288],"existing":[290],"methods.":[291]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}