{"id":"https://openalex.org/W2907166702","doi":"https://doi.org/10.1109/pimrc.2018.8580857","title":"Interference Source Identification for IEEE 802.15.4 wireless Sensor Networks Using Deep Learning","display_name":"Interference Source Identification for IEEE 802.15.4 wireless Sensor Networks Using Deep Learning","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2907166702","doi":"https://doi.org/10.1109/pimrc.2018.8580857","mag":"2907166702"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc.2018.8580857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc.2018.8580857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","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/A5004835193","display_name":"Yi Su","orcid":"https://orcid.org/0000-0002-1946-8063"},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Su Yi","raw_affiliation_strings":["Fujitsu Research and Development Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Research and Development Center, Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014887356","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0001-6996-2134"},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Fujitsu Research and Development Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Research and Development Center, Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101607391","display_name":"Wenqian Xue","orcid":"https://orcid.org/0000-0002-2842-0379"},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqian Xue","raw_affiliation_strings":["Fujitsu Research and Development Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Research and Development Center, Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076904370","display_name":"Xiaojing Fan","orcid":"https://orcid.org/0000-0003-3833-4332"},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojing Fan","raw_affiliation_strings":["Fujitsu Research and Development Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Research and Development Center, Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045179383","display_name":"Lefei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lefei Wang","raw_affiliation_strings":["Fujitsu Research and Development Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Research and Development Center, Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023476533","display_name":"Junfang Tian","orcid":"https://orcid.org/0000-0001-9555-0387"},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Tian","raw_affiliation_strings":["Fujitsu Research and Development Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Research and Development Center, Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039920071","display_name":"Ryuichi Matsukura","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryuichi Matsukura","raw_affiliation_strings":["Fujitsu Laboratories Ltd., Kawasaki, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Laboratories Ltd., Kawasaki, Japan","institution_ids":["https://openalex.org/I2252096349"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"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":0.9994000196456909,"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":0.9994000196456909,"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/T11158","display_name":"Wireless Networks and Protocols","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.9958000183105469,"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/computer-science","display_name":"Computer science","score":0.7612914443016052},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.6493365168571472},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6426731944084167},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.5878025889396667},{"id":"https://openalex.org/keywords/ieee-802.15","display_name":"IEEE 802.15","score":0.49322766065597534},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.46795332431793213},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4627504348754883},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4464268386363983},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4427235722541809},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.41777941584587097},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.39354366064071655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37187862396240234},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2123982310295105},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.08251628279685974}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7612914443016052},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.6493365168571472},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6426731944084167},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.5878025889396667},{"id":"https://openalex.org/C2780407094","wikidata":"https://www.wikidata.org/wiki/Q3267095","display_name":"IEEE 802.15","level":3,"score":0.49322766065597534},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.46795332431793213},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4627504348754883},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4464268386363983},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4427235722541809},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.41777941584587097},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.39354366064071655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37187862396240234},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2123982310295105},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.08251628279685974},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc.2018.8580857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc.2018.8580857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","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":18,"referenced_works":["https://openalex.org/W1922632032","https://openalex.org/W1979589664","https://openalex.org/W2014741474","https://openalex.org/W2041326066","https://openalex.org/W2066200198","https://openalex.org/W2091480865","https://openalex.org/W2096587965","https://openalex.org/W2112796928","https://openalex.org/W2123536775","https://openalex.org/W2480295938","https://openalex.org/W2591951844","https://openalex.org/W2770268514","https://openalex.org/W2775383661","https://openalex.org/W2791522365","https://openalex.org/W2896556344","https://openalex.org/W4250164123","https://openalex.org/W6640109780","https://openalex.org/W6748690524"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4291897433","https://openalex.org/W3011074480","https://openalex.org/W3192840557"],"abstract_inverted_index":{"Due":[0],"to":[1,77,114],"the":[2,80,84,116,121,140,145],"interference":[3,24,57,117,147],"issue":[4],"in":[5,51],"unlicensed":[6],"band,":[7],"sensor":[8,32],"nodes":[9],"frequently":[10],"encounter":[11],"degraded":[12],"performance":[13],"or":[14],"lack":[15],"of":[16,65,83],"connection.":[17],"This":[18],"paper":[19],"provides":[20],"a":[21,90,109],"real-time":[22],"external":[23],"source":[25,58,118],"classification":[26],"method":[27],"for":[28,41],"an":[29,52],"802.15.4-based":[30],"wireless":[31],"network":[33,93],"using":[34,99],"deep":[35,91,122],"learning.":[36],"It":[37],"uses":[38],"RSSI":[39,101],"sampling":[40],"collecting":[42],"training":[43],"data":[44,50],"as":[45,47,103],"well":[46],"online":[48],"test":[49],"office":[53],"environment.":[54],"The":[55],"output":[56],"type":[59],"includes":[60],"Wi-Fi":[61],"beacon,":[62],"different":[63],"classes":[64],"WLAN":[66],"traffic,":[67],"BLE":[68],"iBeacon,":[69],"and":[70,108,132],"microwave":[71],"oven.":[72],"Wireless":[73],"sniffers":[74],"are":[75,112],"used":[76],"help":[78],"labeling":[79],"ground":[81],"truth":[82],"sample":[85],"data.":[86],"We":[87],"have":[88],"trained":[89],"neural":[92],"with":[94,149],"two":[95],"hidden":[96],"convolutional":[97],"layers":[98],"raw":[100],"samples":[102],"inputs.":[104],"A":[105],"micro-level":[106],"model":[107,111],"macro-level":[110],"provided":[113],"predict":[115],"based":[119],"on":[120,127],"learning":[123],"result.":[124],"With":[125],"implementation":[126],"both":[128],"IEEE":[129],"802.15.4":[130],"SoC":[131],"Linux-based":[133],"system,":[134],"our":[135],"experimental":[136],"results":[137],"show":[138],"that":[139],"proposed":[141],"framework":[142],"can":[143],"classify":[144],"major":[146],"types":[148],"high":[150],"accuracy.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}