{"id":"https://openalex.org/W4416250281","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227273","title":"GraphLIP: Graph-Enhanced Lightweight Indoor Positioning Model Leveraging Channel State Information","display_name":"GraphLIP: Graph-Enhanced Lightweight Indoor Positioning Model Leveraging Channel State Information","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250281","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227273"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5082522896","display_name":"Chuhao Chen","orcid":"https://orcid.org/0009-0003-6286-8964"},"institutions":[{"id":"https://openalex.org/I4210118629","display_name":"NARI Group (China)","ror":"https://ror.org/02egn3136","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuhao Chen","raw_affiliation_strings":["Jiangsu Automation Research Institute,Lianyungang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Automation Research Institute,Lianyungang,China","institution_ids":["https://openalex.org/I4210118629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102715927","display_name":"Zihan Zhou","orcid":"https://orcid.org/0000-0002-9034-0951"},"institutions":[{"id":"https://openalex.org/I7350606","display_name":"Dalian Jiaotong University","ror":"https://ror.org/05gp45n31","country_code":"CN","type":"education","lineage":["https://openalex.org/I7350606"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihan Zhou","raw_affiliation_strings":["Dalian Jiaotong University,School of Track Intelligent Engineering,Dalian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian Jiaotong University,School of Track Intelligent Engineering,Dalian,China","institution_ids":["https://openalex.org/I7350606"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100609608","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0002-5214-217X"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["Harbin Engineering University,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,Harbin,China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100318321","display_name":"Wei Li","orcid":"https://orcid.org/0000-0002-9428-1784"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Harbin Engineering University,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,Harbin,China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080015931","display_name":"Xiangxu Meng","orcid":"https://orcid.org/0000-0001-9842-4044"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangxu Meng","raw_affiliation_strings":["Harbin Engineering University,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,Harbin,China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9516000151634216,"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":0.9516000151634216,"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/T10655","display_name":"GNSS positioning and interference","score":0.010499999858438969,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.004800000227987766,"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/multipath-propagation","display_name":"Multipath propagation","score":0.6794000267982483},{"id":"https://openalex.org/keywords/gnss-applications","display_name":"GNSS applications","score":0.46860000491142273},{"id":"https://openalex.org/keywords/indoor-positioning-system","display_name":"Indoor positioning system","score":0.4115000069141388},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.4047999978065491},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4002000093460083},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.38350000977516174},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.3797999918460846},{"id":"https://openalex.org/keywords/positioning-technology","display_name":"Positioning technology","score":0.36169999837875366},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.35569998621940613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7279999852180481},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.6794000267982483},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.49790000915527344},{"id":"https://openalex.org/C14279187","wikidata":"https://www.wikidata.org/wiki/Q5514012","display_name":"GNSS applications","level":3,"score":0.46860000491142273},{"id":"https://openalex.org/C2777486483","wikidata":"https://www.wikidata.org/wiki/Q6026477","display_name":"Indoor positioning system","level":3,"score":0.4115000069141388},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.4047999978065491},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4002000093460083},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C2778075934","wikidata":"https://www.wikidata.org/wiki/Q17141406","display_name":"Positioning technology","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.35569998621940613},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C187394410","wikidata":"https://www.wikidata.org/wiki/Q17141406","display_name":"Hybrid positioning system","level":4,"score":0.3434000015258789},{"id":"https://openalex.org/C155292070","wikidata":"https://www.wikidata.org/wiki/Q1198122","display_name":"Location-based service","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32820001244544983},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3149999976158142},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C202311505","wikidata":"https://www.wikidata.org/wiki/Q1474701","display_name":"Radio propagation","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C166212672","wikidata":"https://www.wikidata.org/wiki/Q2165162","display_name":"GNSS augmentation","level":4,"score":0.29499998688697815},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C95491727","wikidata":"https://www.wikidata.org/wiki/Q992968","display_name":"Mobile telephony","level":3,"score":0.2583000063896179},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":28,"referenced_works":["https://openalex.org/W2044846595","https://openalex.org/W2143228105","https://openalex.org/W2309512289","https://openalex.org/W2605943641","https://openalex.org/W2623902153","https://openalex.org/W2739582838","https://openalex.org/W2888967269","https://openalex.org/W2890784233","https://openalex.org/W2963145597","https://openalex.org/W2967101465","https://openalex.org/W2975183578","https://openalex.org/W2999043856","https://openalex.org/W2999209556","https://openalex.org/W3040211795","https://openalex.org/W3043866295","https://openalex.org/W3045610411","https://openalex.org/W3155725449","https://openalex.org/W3163879725","https://openalex.org/W3167976421","https://openalex.org/W3170853162","https://openalex.org/W3171038842","https://openalex.org/W4205533812","https://openalex.org/W4226360729","https://openalex.org/W4292672216","https://openalex.org/W4297005482","https://openalex.org/W4377235641","https://openalex.org/W4387415289","https://openalex.org/W4404738374"],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,15,68,102,141,144],"demand":[4],"for":[5,64],"indoor":[6,30,65,94,118,150],"positioning":[7,95,119],"services":[8],"has":[9],"surged":[10],"due":[11],"to":[12,28],"urbanization":[13],"and":[14,128],"widespread":[16],"use":[17],"of":[18,70,143],"mobile":[19],"devices.":[20],"Unlike":[21],"outdoor":[22],"environments,":[23],"where":[24],"GNSS":[25],"signals":[26],"struggle":[27],"penetrate":[29],"spaces,":[31],"traditional":[32],"RSSI-based":[33],"fingerprinting":[34],"methods":[35,88],"encounter":[36],"challenges":[37,73],"posed":[38],"by":[39,44],"severe":[40],"signal":[41,58],"attenuation":[42],"caused":[43],"multipath":[45],"effects.":[46],"Channel":[47],"State":[48],"Information":[49],"(CSI)":[50],"emerges":[51],"as":[52],"a":[53,116,122,129],"promising":[54],"alternative,":[55],"offering":[56],"fine-grained":[57],"propagation":[59],"characteristics":[60],"that":[61],"are":[62],"advantageous":[63],"positioning.":[66,151],"Despite":[67],"potential":[69],"CSI-based":[71],"positioning,":[72],"remain":[74],"in":[75,92,107,147],"effectively":[76],"capturing":[77],"features":[78],"from":[79],"CSI":[80],"matrices":[81],"with":[82],"high":[83],"aspect":[84],"ratios.":[85],"Deep":[86],"learning":[87],"have":[89],"gained":[90],"traction":[91],"addressing":[93],"challenges,":[96],"yet":[97],"existing":[98],"approaches":[99],"often":[100],"overlook":[101],"correlation":[103],"between":[104],"different":[105],"subcarriers":[106],"CSI.":[108],"To":[109],"address":[110],"these":[111],"issues,":[112],"this":[113],"paper":[114],"proposes":[115],"lightweight":[117],"model":[120,146],"comprising":[121],"convolutional":[123],"reparameterization-based":[124],"feature":[125],"fusion":[126],"module":[127,132],"spatial":[130],"modeling":[131],"based":[133],"on":[134],"graph":[135],"neural":[136],"networks.":[137],"Experimental":[138],"results":[139],"demonstrate":[140],"effectiveness":[142],"proposed":[145],"achieving":[148],"high-precision":[149]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}
