{"id":"https://openalex.org/W4387872887","doi":"https://doi.org/10.1109/secon58729.2023.10287483","title":"Learning-based Techniques for Transmitter Localization: A Case Study on Model Robustness","display_name":"Learning-based Techniques for Transmitter Localization: A Case Study on Model Robustness","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4387872887","doi":"https://doi.org/10.1109/secon58729.2023.10287483"},"language":"en","primary_location":{"id":"doi:10.1109/secon58729.2023.10287483","is_oa":false,"landing_page_url":"https://doi.org/10.1109/secon58729.2023.10287483","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","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/A5046494066","display_name":"Frost Mitchell","orcid":"https://orcid.org/0000-0002-2542-5836"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Frost Mitchell","raw_affiliation_strings":["University of Utah,Salt Lake City,USA","University of Utah, Salt Lake City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah,Salt Lake City,USA","institution_ids":["https://openalex.org/I223532165"]},{"raw_affiliation_string":"University of Utah, Salt Lake City, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068259004","display_name":"Neal Patwari","orcid":"https://orcid.org/0000-0003-3440-2043"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neal Patwari","raw_affiliation_strings":["Washington University in St. Louis,St. Louis,USA","Washington University in St. Louis, St. Louis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Washington University in St. Louis,St. Louis,USA","institution_ids":["https://openalex.org/I204465549"]},{"raw_affiliation_string":"Washington University in St. Louis, St. Louis, USA","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014414126","display_name":"Aditya Bhaskara","orcid":"https://orcid.org/0000-0001-5505-3140"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aditya Bhaskara","raw_affiliation_strings":["University of Utah,Salt Lake City,USA","University of Utah, Salt Lake City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah,Salt Lake City,USA","institution_ids":["https://openalex.org/I223532165"]},{"raw_affiliation_string":"University of Utah, Salt Lake City, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000720324","display_name":"Sneha Kumar Kasera","orcid":"https://orcid.org/0000-0002-5589-748X"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sneha Kumar Kasera","raw_affiliation_strings":["University of Utah,Salt Lake City,USA","University of Utah, Salt Lake City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah,Salt Lake City,USA","institution_ids":["https://openalex.org/I223532165"]},{"raw_affiliation_string":"University of Utah, Salt Lake City, USA","institution_ids":["https://openalex.org/I223532165"]}]}],"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":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"133","last_page":"141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9995999932289124,"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":0.9995999932289124,"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/T10860","display_name":"Speech and Audio Processing","score":0.9961000084877014,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/transmitter","display_name":"Transmitter","score":0.8900585174560547},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8811914324760437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7545626163482666},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5914587378501892},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5841152667999268},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.4833680987358093},{"id":"https://openalex.org/keywords/shadow-mapping","display_name":"Shadow mapping","score":0.4572271406650543},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.40760719776153564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3284892439842224},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.16367781162261963},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15932342410087585},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.13758811354637146}],"concepts":[{"id":"https://openalex.org/C47798520","wikidata":"https://www.wikidata.org/wiki/Q190157","display_name":"Transmitter","level":3,"score":0.8900585174560547},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8811914324760437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7545626163482666},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5914587378501892},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5841152667999268},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.4833680987358093},{"id":"https://openalex.org/C116544410","wikidata":"https://www.wikidata.org/wiki/Q1478122","display_name":"Shadow mapping","level":2,"score":0.4572271406650543},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.40760719776153564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3284892439842224},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.16367781162261963},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15932342410087585},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.13758811354637146},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/secon58729.2023.10287483","is_oa":false,"landing_page_url":"https://doi.org/10.1109/secon58729.2023.10287483","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2794103424","https://openalex.org/W4245435724","https://openalex.org/W1996530509","https://openalex.org/W3028317537","https://openalex.org/W2389515972","https://openalex.org/W2055301889","https://openalex.org/W1505959757","https://openalex.org/W2376554934","https://openalex.org/W2077790809","https://openalex.org/W2906246018"],"abstract_inverted_index":{"Transmitter":[0,192],"localization":[1,22,82,145],"remains":[2],"a":[3,27,32,96,106,141],"challenging":[4],"problem":[5],"in":[6,23,105,130,179],"large-scale":[7,87],"outdoor":[8,110],"environments,":[9],"especially":[10],"when":[11],"transmitters":[12,67],"and":[13,116,126,128,135,168,201],"receivers":[14,115],"are":[15,69,123,177],"allowed":[16],"to":[17,161],"be":[18,52],"mobile.":[19],"We":[20,184],"consider":[21],"the":[24,61,84,163],"context":[25],"of":[26,86,132,165,172],"Radio":[28],"Dynamic":[29],"Zone":[30],"(RDZ),":[31],"proposed":[33],"experimental":[34,40],"platform":[35],"where":[36],"researchers":[37],"can":[38,148],"deploy":[39],"devices,":[41],"waveforms,":[42],"or":[43],"wireless":[44],"networks.":[45],"Wireless":[46],"users":[47],"outside":[48],"an":[49],"RDZ":[50],"must":[51],"protected":[53],"from":[54,58,151],"harmful":[55],"interference":[56,71],"coming":[57],"sources":[59],"inside":[60],"RDZ.":[62],"In":[63],"this":[64],"setting,":[65],"localizing":[66],"that":[68,147,176,186],"causing":[70],"is":[72,83,194],"critical.":[73],"One":[74],"notable":[75],"obstacle":[76],"for":[77,81,99],"developing":[78],"data-driven":[79],"methods":[80,206],"lack":[85],"training":[88],"datasets.":[89],"As":[90],"our":[91,158,166,187],"first":[92],"contribution,":[93],"we":[94,139,156],"present":[95],"new":[97,142,159],"dataset":[98,160],"localization,":[100],"captured":[101],"at":[102],"462.7":[103],"MHz":[104],"4":[107],"sq.":[108],"km":[109],"area":[111],"with":[112],"29":[113],"different":[114],"over":[117],"4,500":[118],"unique":[119],"transmitter":[120],"locations.":[121],"Receivers":[122],"both":[124],"mobile":[125],"stationary,":[127],"heterogeneous":[129,153],"terms":[131],"hardware,":[133],"placement,":[134],"gain":[136],"settings.":[137],"Next,":[138],"propose":[140],"machine":[143],"learning-based":[144],"method":[146],"handle":[149],"inputs":[150,175],"uncalibrated,":[152],"receivers.":[154],"Finally,":[155],"leverage":[157],"study":[162],"robustness":[164],"technique":[167],"others":[169],"against":[170],"\u201cout":[171],"distribution\u201d":[173],"(OOD)":[174],"common":[178],"most":[180],"real":[181],"life":[182],"applications.":[183],"show":[185],"technique,":[188],"CUTL":[189],"(Calibrated":[190],"U-Net":[191],"Localization),":[193],"49%":[195],"more":[196,202],"accurate":[197],"on":[198,207],"in-distribution":[199],"data,":[200],"robust":[203],"than":[204],"previous":[205],"OOD":[208],"data.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
