{"id":"https://openalex.org/W2963219425","doi":"https://doi.org/10.1109/iwcmc.2019.8766734","title":"Wireless Neural Network: Enabling Neural Computing over Wireless Sensor Network Based on Superposition Transmissions","display_name":"Wireless Neural Network: Enabling Neural Computing over Wireless Sensor Network Based on Superposition Transmissions","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2963219425","doi":"https://doi.org/10.1109/iwcmc.2019.8766734","mag":"2963219425"},"language":"en","primary_location":{"id":"doi:10.1109/iwcmc.2019.8766734","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc.2019.8766734","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 15th International Wireless Communications &amp; Mobile Computing Conference (IWCMC)","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/A5118969714","display_name":"He Wang","orcid":"https://orcid.org/0009-0000-3221-7165"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Wang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100771966","display_name":"Xiangming Li","orcid":"https://orcid.org/0000-0003-3128-6219"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangming Li","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017996057","display_name":"Neng Ye","orcid":"https://orcid.org/0000-0002-6605-826X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Neng Ye","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100449548","display_name":"Aihua Wang","orcid":"https://orcid.org/0000-0002-6304-5201"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aihua Wang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.7965,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63433193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1913","last_page":"1917"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9994999766349792,"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":0.9994999766349792,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9994000196456909,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9987000226974487,"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/computer-science","display_name":"Computer science","score":0.773293137550354},{"id":"https://openalex.org/keywords/key-distribution-in-wireless-sensor-networks","display_name":"Key distribution in wireless sensor networks","score":0.6602078676223755},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.6246556043624878},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.6175022721290588},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.5902866125106812},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.5803501605987549},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5585920214653015},{"id":"https://openalex.org/keywords/radio-resource-management","display_name":"Radio resource management","score":0.5075958967208862},{"id":"https://openalex.org/keywords/superposition-principle","display_name":"Superposition principle","score":0.4889160692691803},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4263085424900055},{"id":"https://openalex.org/keywords/data-transmission","display_name":"Data transmission","score":0.4140962064266205},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.39910563826560974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2138521671295166},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1709158718585968},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1276804506778717}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.773293137550354},{"id":"https://openalex.org/C41971633","wikidata":"https://www.wikidata.org/wiki/Q6398155","display_name":"Key distribution in wireless sensor networks","level":4,"score":0.6602078676223755},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.6246556043624878},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.6175022721290588},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.5902866125106812},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.5803501605987549},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5585920214653015},{"id":"https://openalex.org/C182448111","wikidata":"https://www.wikidata.org/wiki/Q7281197","display_name":"Radio resource management","level":4,"score":0.5075958967208862},{"id":"https://openalex.org/C27753989","wikidata":"https://www.wikidata.org/wiki/Q284885","display_name":"Superposition principle","level":2,"score":0.4889160692691803},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4263085424900055},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.4140962064266205},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.39910563826560974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2138521671295166},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1709158718585968},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1276804506778717},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwcmc.2019.8766734","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc.2019.8766734","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 15th International Wireless Communications &amp; Mobile Computing Conference (IWCMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1996804779","https://openalex.org/W2001495973","https://openalex.org/W2110811672","https://openalex.org/W2131049857","https://openalex.org/W2142246654","https://openalex.org/W2273675851","https://openalex.org/W2591079949","https://openalex.org/W2745051223","https://openalex.org/W2758956933","https://openalex.org/W2769502706","https://openalex.org/W2775400508","https://openalex.org/W2807813999","https://openalex.org/W2891466177","https://openalex.org/W2899478246","https://openalex.org/W2900452440","https://openalex.org/W2919115771","https://openalex.org/W2962836907"],"related_works":["https://openalex.org/W2037910509","https://openalex.org/W2132921191","https://openalex.org/W4226410209","https://openalex.org/W1569013426","https://openalex.org/W2520703208","https://openalex.org/W2386645218","https://openalex.org/W1555537460","https://openalex.org/W2610266344","https://openalex.org/W2725652413","https://openalex.org/W1617165411"],"abstract_inverted_index":{"Wireless":[0],"sensor":[1],"network":[2,68,95,128],"(WSN)":[3],"is":[4,104],"a":[5,26,44,58,65],"key":[6],"enabling":[7],"technology":[8],"for":[9,29,56],"Internet":[10],"of":[11,46,83,102,115,126],"Things":[12],"(IoT),":[13],"where":[14,111],"the":[15,20,35,72,80,89,112,124,144,149],"sensed":[16,52],"data":[17,53],"reported":[18],"by":[19,78,107],"distributed":[21],"sensors":[22],"are":[23,54],"transmitted":[24],"to":[25,43,70,122,158],"core":[27],"node":[28],"intelligent":[30],"computation":[31],"and":[32,40,75,96],"decision.":[33,61],"However,":[34],"isolation":[36],"between":[37,91],"wireless":[38,66,76],"communication":[39,77],"computing":[41,74],"leads":[42],"waste":[45],"radio":[47,84,150],"resources,":[48],"since":[49],"not":[50],"all":[51],"required":[55],"making":[57],"precise":[59],"enough":[60],"Hence,":[62],"we":[63],"propose":[64],"neural":[67,73,94],"(WNN)":[69],"integrate":[71],"exploiting":[79],"superposition":[81,159],"characteristics":[82],"channels":[85],"as":[86,88],"well":[87],"reciprocity":[90],"deep":[92],"artificial":[93],"multi-tier":[97],"WSN.":[98],"The":[99],"learning":[100],"ability":[101],"WNN":[103],"further":[105],"enhanced":[106],"introducing":[108],"multi-carrier":[109],"transmission":[110],"transmit":[113],"gain":[114],"each":[116],"sub-carrier":[117],"can":[118,139,153],"be":[119,140,154],"freely":[120],"trained":[121],"increase":[123],"number":[125],"adjustable":[127],"parameters.":[129],"Experiments":[130],"on":[131],"some":[132],"datasets":[133],"demonstrate":[134],"that,":[135],"similar":[136],"decision":[137],"accuracy":[138],"achieved":[141],"compared":[142],"with":[143],"conventional":[145],"isolated":[146],"method,":[147],"while":[148],"resource":[151],"consumption":[152],"greatly":[155],"reduced":[156],"due":[157],"transmissions.":[160]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
