{"id":"https://openalex.org/W4309228627","doi":"https://doi.org/10.1109/icnp55882.2022.9940424","title":"CONST: Exploiting Spatial-Temporal Correlation for Multi-Gateway based Reliable LoRa Reception","display_name":"CONST: Exploiting Spatial-Temporal Correlation for Multi-Gateway based Reliable LoRa Reception","publication_year":2022,"publication_date":"2022-10-30","ids":{"openalex":"https://openalex.org/W4309228627","doi":"https://doi.org/10.1109/icnp55882.2022.9940424"},"language":"en","primary_location":{"id":"doi:10.1109/icnp55882.2022.9940424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp55882.2022.9940424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 30th International Conference on Network Protocols (ICNP)","raw_type":"proceedings-article"},"type":"article","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/A5100358736","display_name":"Zeyu Zhang","orcid":"https://orcid.org/0000-0002-7157-6272"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zeyu Zhang","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100367141","display_name":"Weiwei Chen","orcid":"https://orcid.org/0000-0003-3359-0556"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weiwei Chen","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100704433","display_name":"Junwen Wang","orcid":"https://orcid.org/0000-0002-4432-4707"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junwen Wang","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100328284","display_name":"Shuai Wang","orcid":"https://orcid.org/0000-0002-3609-2205"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuai Wang","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038811034","display_name":"Tian He","orcid":"https://orcid.org/0000-0001-6062-2619"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian He","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100358736"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0978,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.76550348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12079","display_name":"IoT Networks and Protocols","score":1.0,"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/T12079","display_name":"IoT Networks and Protocols","score":1.0,"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/T11932","display_name":"Wireless Body Area Networks","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12801","display_name":"Bluetooth and Wireless Communication Technologies","score":0.9872000217437744,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.835053026676178},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.6052994728088379},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5786116123199463},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5216615200042725},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.4904756247997284},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4711529016494751},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.44063496589660645},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.4135134816169739},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.28059887886047363},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.24901646375656128},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1636078655719757}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.835053026676178},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.6052994728088379},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5786116123199463},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5216615200042725},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.4904756247997284},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4711529016494751},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.44063496589660645},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.4135134816169739},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.28059887886047363},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.24901646375656128},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1636078655719757},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnp55882.2022.9940424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp55882.2022.9940424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 30th International Conference on Network Protocols (ICNP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8799999952316284,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1875616701","display_name":null,"funder_award_id":"61902066","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8818265435","display_name":null,"funder_award_id":"BK20190336","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G8926446059","display_name":null,"funder_award_id":"2018YFB2100302","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2520480241","https://openalex.org/W2558305529","https://openalex.org/W2597831797","https://openalex.org/W2794682992","https://openalex.org/W2798521665","https://openalex.org/W2807797415","https://openalex.org/W2898178166","https://openalex.org/W2908017346","https://openalex.org/W2962691290","https://openalex.org/W2991230344","https://openalex.org/W3006550663","https://openalex.org/W3007760816","https://openalex.org/W3018719010","https://openalex.org/W3032964970","https://openalex.org/W3047340865","https://openalex.org/W3106830511","https://openalex.org/W3109569612","https://openalex.org/W3110221271","https://openalex.org/W3193982829","https://openalex.org/W3198632567","https://openalex.org/W3214172595","https://openalex.org/W6730505117"],"related_works":["https://openalex.org/W1496222301","https://openalex.org/W3207760230","https://openalex.org/W1590307681","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2358353312","https://openalex.org/W2353836703","https://openalex.org/W41015297","https://openalex.org/W4280645561","https://openalex.org/W1671936420"],"abstract_inverted_index":{"As":[0],"a":[1,106,133],"representative":[2],"technology":[3],"of":[4,120],"low":[5],"power":[6],"wide":[7],"area":[8],"network,":[9],"LoRa":[10,22,46,68,134,142],"has":[11],"been":[12],"widely":[13],"adopted":[14],"to":[15,25,70,115,126],"many":[16],"applications.":[17],"A":[18],"fundamental":[19],"question":[20],"in":[21,30,67,132,151],"is":[23,113],"how":[24],"improve":[26],"its":[27],"reception":[28,47],"quality":[29],"ultra-low":[31],"SNR":[32],"scenarios.":[33],"Different":[34],"from":[35,99],"existing":[36,179],"studies":[37],"that":[38,76,161],"exploit":[39,61],"either":[40],"spatial":[41,63],"or":[42],"temporal":[43,65],"correlation":[44,56,66],"for":[45],"recovery,":[48],"this":[49],"paper":[50],"jointly":[51,71],"leverages":[52],"the":[53,62,77,117,124,129],"fine-grained":[54,78],"spatial-temporal":[55],"among":[57],"multiple":[58,100],"gateways.":[59],"We":[60,136],"and":[64,89,97,147,154,170],"packets":[69],"process":[72],"received":[73],"signals":[74,98],"so":[75],"offsets":[79],"including":[80],"Central":[81],"Frequency":[82,91],"Offset":[83,87,92],"(CFO),":[84],"Sampling":[85,90],"Time":[86],"(STO)":[88],"(SFO)":[93],"are":[94,102],"well":[95],"compensated,":[96],"gateways":[101,148],"combined":[103],"coherently.":[104],"Moreover,":[105],"deep":[107],"learning":[108],"based":[109],"soft":[110],"decoding":[111],"scheme":[112],"developed":[114],"integrate":[116],"energy":[118],"distribution":[119],"each":[121],"symbol":[122],"into":[123],"decoder":[125],"further":[127],"enhance":[128],"coding":[130],"gain":[131],"packet.":[135],"evaluate":[137],"our":[138,162],"work":[139,163],"with":[140,178],"commodity":[141],"devices":[143],"(i.e.,":[144,149],"Semtech":[145],"SX1278)":[146],"USRP-B210)":[150],"both":[152],"indoor":[153],"outdoor":[155],"environments.":[156],"Extensive":[157],"experiment":[158],"results":[159],"show":[160],"achieves":[164],"4.6dB":[165],"higher":[166],"signal-to-noise":[167],"ratio":[168],"(SNR)":[169],"1.5\u00d7":[171],"lower":[172],"bit":[173],"error":[174],"rate":[175],"(BER)":[176],"compared":[177],"approaches.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
