{"id":"https://openalex.org/W4312450256","doi":"https://doi.org/10.1109/ipin54987.2022.9918112","title":"A Framework for CSI-Based Indoor Localization with ID Convolutional Neural Networks","display_name":"A Framework for CSI-Based Indoor Localization with ID Convolutional Neural Networks","publication_year":2022,"publication_date":"2022-09-05","ids":{"openalex":"https://openalex.org/W4312450256","doi":"https://doi.org/10.1109/ipin54987.2022.9918112"},"language":"en","primary_location":{"id":"doi:10.1109/ipin54987.2022.9918112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipin54987.2022.9918112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN)","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/A5100402258","display_name":"Liping Wang","orcid":"https://orcid.org/0000-0002-5526-0868"},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liping Wang","raw_affiliation_strings":["Colorado State University,Department of Electrical and Computer Engineering,Fort Collins,CO,United States","Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Colorado State University,Department of Electrical and Computer Engineering,Fort Collins,CO,United States","institution_ids":["https://openalex.org/I92446798"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, United States","institution_ids":["https://openalex.org/I92446798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018382547","display_name":"Sudeep Pasricha","orcid":"https://orcid.org/0000-0002-0846-0066"},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sudeep Pasricha","raw_affiliation_strings":["Colorado State University,Department of Electrical and Computer Engineering,Fort Collins,CO,United States","Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Colorado State University,Department of Electrical and Computer Engineering,Fort Collins,CO,United States","institution_ids":["https://openalex.org/I92446798"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, United States","institution_ids":["https://openalex.org/I92446798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I92446798"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9940000176429749,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/computer-science","display_name":"Computer science","score":0.8293412923812866},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.8080236911773682},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.621674120426178},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5608538389205933},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5059100985527039},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48882147669792175},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42801064252853394},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4153679609298706},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.38698697090148926},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.323861300945282},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.2628387212753296},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.18992853164672852}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8293412923812866},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.8080236911773682},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.621674120426178},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5608538389205933},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5059100985527039},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48882147669792175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42801064252853394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4153679609298706},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.38698697090148926},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.323861300945282},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.2628387212753296},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.18992853164672852}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipin54987.2022.9918112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipin54987.2022.9918112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G7664534584","display_name":null,"funder_award_id":"CNS-2132385","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/W2044846595","https://openalex.org/W2128190945","https://openalex.org/W2161160262","https://openalex.org/W2271840356","https://openalex.org/W2309512289","https://openalex.org/W2739582838","https://openalex.org/W2805779987","https://openalex.org/W2834022868","https://openalex.org/W2900742918","https://openalex.org/W2901531104","https://openalex.org/W2924873290","https://openalex.org/W2952065976","https://openalex.org/W2979431265","https://openalex.org/W2980021985","https://openalex.org/W3179065261","https://openalex.org/W3201629247","https://openalex.org/W3215319504","https://openalex.org/W4287208731","https://openalex.org/W4312338993","https://openalex.org/W6638444622","https://openalex.org/W6694517276","https://openalex.org/W6794513498","https://openalex.org/W6798033975"],"related_works":["https://openalex.org/W3093612317","https://openalex.org/W2613736958","https://openalex.org/W4287776258","https://openalex.org/W3027997911","https://openalex.org/W2175746458","https://openalex.org/W2732542196","https://openalex.org/W2760085659","https://openalex.org/W2883200793","https://openalex.org/W2738221750","https://openalex.org/W3012978760"],"abstract_inverted_index":{"Modern":[0],"indoor":[1,13,27,45,69,124,158],"localization":[2,28,159],"techniques":[3],"are":[4],"essential":[5],"to":[6,60,66,99,109,137,150],"overcome":[7],"the":[8,40,62,151],"weak":[9],"GPS":[10],"coverage":[11],"in":[12,21,39],"environments.":[14],"Recently,":[15],"considerable":[16],"progress":[17],"has":[18],"been":[19],"made":[20],"Channel":[22],"State":[23,128],"Information":[24],"(CSI)":[25],"based":[26],"with":[29,47,96,115,144],"signal":[30,34],"fingerprints.":[31],"However,":[32],"CSI":[33,65,97,113],"patterns":[35],"can":[36],"be":[37],"complicated":[38],"large":[41,117],"and":[42,86,107,156],"highly":[43],"dynamic":[44],"spaces":[46],"complex":[48,123],"interiors,":[49],"thus":[50],"a":[51,67,87,112,116],"solution":[52,78],"for":[53],"solving":[54],"this":[55,72,101],"issue":[56],"is":[57],"urgently":[58],"needed":[59],"expand":[61],"applications":[63],"of":[64,119,147],"broader":[68],"space.":[70],"In":[71],"paper,":[73],"we":[74],"propose":[75],"an":[76],"end-to-end":[77],"including":[79],"data":[80,120],"collection,":[81],"pattern":[82],"clustering,":[83],"denoising,":[84],"calibration":[85],"lightweight":[88],"one-dimensional":[89],"convolutional":[90],"neural":[91],"network":[92],"(1D":[93],"CNN)":[94],"model":[95],"fingerprinting":[98],"tackle":[100],"problem.":[102],"We":[103],"have":[104],"also":[105],"created":[106],"plan":[108],"open":[110],"source":[111],"dataset":[114],"amount":[118],"collected":[121],"across":[122],"environments":[125],"at":[126],"Colorado":[127],"University.":[129],"Experiments":[130],"indicate":[131],"that":[132],"our":[133],"approach":[134],"achieves":[135],"up":[136],"68.5%":[138],"improved":[139],"performance":[140],"(mean":[141],"distance":[142],"error)":[143],"minimal":[145],"number":[146],"parameters,":[148],"compared":[149],"best-known":[152],"deep":[153],"machine":[154],"learning":[155],"CSI-based":[157],"works.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}