{"id":"https://openalex.org/W2992557910","doi":"https://doi.org/10.1109/jiot.2019.2957964","title":"Gaussian Data-Aided Sensing With Multichannel Random Access and Model Selection","display_name":"Gaussian Data-Aided Sensing With Multichannel Random Access and Model Selection","publication_year":2019,"publication_date":"2019-12-05","ids":{"openalex":"https://openalex.org/W2992557910","doi":"https://doi.org/10.1109/jiot.2019.2957964","mag":"2992557910"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2019.2957964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2019.2957964","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1912.02298","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022303970","display_name":"Jinho Choi","orcid":"https://orcid.org/0000-0002-4895-6680"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Jinho Choi","raw_affiliation_strings":["School of Information Technology, Deakin University, Geelong, Australia","Deakin University"],"raw_orcid":"https://orcid.org/0000-0002-4895-6680","affiliations":[{"raw_affiliation_string":"School of Information Technology, Deakin University, Geelong, Australia","institution_ids":["https://openalex.org/I149704539"]},{"raw_affiliation_string":"Deakin University","institution_ids":["https://openalex.org/I149704539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022303970"],"corresponding_institution_ids":["https://openalex.org/I149704539"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18422798,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":"3","first_page":"2412","last_page":"2420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9997000098228455,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9955999851226807,"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/gaussian","display_name":"Gaussian","score":0.6783502101898193},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6530566811561584},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.6444779634475708},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5230801701545715},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5057950019836426},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47578346729278564},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46318957209587097},{"id":"https://openalex.org/keywords/random-access","display_name":"Random access","score":0.4457401633262634},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.44236689805984497},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37399908900260925},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15258413553237915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.10891330242156982},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09825989603996277}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6783502101898193},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6530566811561584},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.6444779634475708},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5230801701545715},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5057950019836426},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47578346729278564},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46318957209587097},{"id":"https://openalex.org/C101722063","wikidata":"https://www.wikidata.org/wiki/Q218825","display_name":"Random access","level":2,"score":0.4457401633262634},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.44236689805984497},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37399908900260925},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15258413553237915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10891330242156982},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09825989603996277},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/jiot.2019.2957964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2019.2957964","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1912.02298","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.02298","pdf_url":"https://arxiv.org/pdf/1912.02298","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2992557910","is_oa":true,"landing_page_url":"https://arxiv.org/abs/1912.02298","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:dro.deakin.edu.au:DU:30135885","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401102","display_name":"Own your potential (DEAKIN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149704539","host_organization_name":"Deakin University","host_organization_lineage":["https://openalex.org/I149704539"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},{"id":"pmh:oai:figshare.com:article/20710699","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Gaussian_data-aided_sensing_with_multichannel_random_access_and_model_selection/20710699","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.48550/arxiv.1912.02298","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1912.02298","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1912.02298","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.02298","pdf_url":"https://arxiv.org/pdf/1912.02298","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2992557910.pdf","grobid_xml":"https://content.openalex.org/works/W2992557910.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1493497947","https://openalex.org/W1515851193","https://openalex.org/W1516061453","https://openalex.org/W1595409123","https://openalex.org/W2049934117","https://openalex.org/W2094536313","https://openalex.org/W2111619626","https://openalex.org/W2134295053","https://openalex.org/W2142355131","https://openalex.org/W2145096794","https://openalex.org/W2153643801","https://openalex.org/W2158125716","https://openalex.org/W2166961701","https://openalex.org/W2168571759","https://openalex.org/W2288604723","https://openalex.org/W2296616510","https://openalex.org/W2474071019","https://openalex.org/W2565270582","https://openalex.org/W2613173048","https://openalex.org/W2799061466","https://openalex.org/W2899702797","https://openalex.org/W2940773477","https://openalex.org/W2950929549","https://openalex.org/W3015812362","https://openalex.org/W3146700414","https://openalex.org/W4250598470","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2993398894","https://openalex.org/W3101768045","https://openalex.org/W2953267539","https://openalex.org/W3115192031","https://openalex.org/W2784813279","https://openalex.org/W2951830679","https://openalex.org/W1784471954","https://openalex.org/W2100830973","https://openalex.org/W1508396808","https://openalex.org/W3122906363","https://openalex.org/W2963713839","https://openalex.org/W2558261303","https://openalex.org/W2085160950","https://openalex.org/W2124815084","https://openalex.org/W3103057304","https://openalex.org/W3204500065","https://openalex.org/W3043912163","https://openalex.org/W1523622035","https://openalex.org/W1968377866","https://openalex.org/W3122127688"],"abstract_inverted_index":{"In":[0,74],"this":[1,115],"article,":[2],"we":[3,157],"study":[4],"data-aided":[5],"sensing":[6],"(DAS)":[7],"for":[8,100,107],"a":[9,13,18,26,41,57,65,76,141,145,181,185],"system":[10],"consisting":[11],"of":[12,20,68,78,152],"base":[14],"station":[15],"(BS)":[16],"and":[17,178],"number":[19,67],"nodes,":[21],"where":[22,184],"the":[23,35,52,87,95,127,135,150,153,194],"BS":[24,53,96,136],"becomes":[25],"receiver":[27],"that":[28,37,50,90,109,143],"collects":[29],"measurements":[30,69,108,172],"or":[31],"data":[32,47,88,102,146],"sets":[33,89],"from":[34,97,173],"nodes":[36,79,174],"are":[38,80,91,110],"distributed":[39],"over":[40],"cell.":[42],"DAS":[43,106,119,160],"is":[44,120,137,190],"an":[45],"iterative":[46],"collection":[48],"scheme":[49],"allows":[51],"to":[54,71,122,139,148,170,192],"efficiently":[55],"estimate":[56],"target":[58],"signal":[59],"(i.e.,":[60],"all":[61],"nodes'":[62],"measurements)":[63],"with":[64,112,166,180,197],"small":[66],"(compared":[70],"random":[72,176],"polling).":[73],"DAS,":[75],"set":[77,147],"selected":[81],"in":[82,114,132,161],"each":[83,133],"round":[84],"based":[85],"on":[86],"already":[92],"available":[93],"at":[94],"previous":[98],"rounds":[99],"efficient":[101],"collection.":[103],"We":[104],"consider":[105],"correlated":[111],"Gaussian":[113,124,159],"article.":[116],"The":[117],"resulting":[118],"referred":[121],"as":[123],"DAS.":[125,198],"Using":[126],"mean-squared":[128],"error":[129],"(MSE)":[130],"criterion,":[131],"round,":[134],"able":[138],"choose":[140],"node":[142],"has":[144],"minimize":[149],"MSE":[151],"next":[154],"round.":[155],"Furthermore,":[156],"generalize":[158],"two":[162],"different":[163],"ways:":[164],"1)":[165],"multiple":[167],"parallel":[168],"channels":[169],"upload":[171],"using":[175],"access":[177],"2)":[179],"model":[182,195],"selection,":[183],"multiarmed":[186],"bandit":[187],"problem":[188],"formulation":[189],"used":[191],"combine":[193],"selection":[196]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
