{"id":"https://openalex.org/W4387251028","doi":"https://doi.org/10.1109/meditcom58224.2023.10266628","title":"A Resource-Efficient Asymptotically Equivalent GLRT Test for Radio Source Distributed Detection","display_name":"A Resource-Efficient Asymptotically Equivalent GLRT Test for Radio Source Distributed Detection","publication_year":2023,"publication_date":"2023-09-04","ids":{"openalex":"https://openalex.org/W4387251028","doi":"https://doi.org/10.1109/meditcom58224.2023.10266628"},"language":"en","primary_location":{"id":"doi:10.1109/meditcom58224.2023.10266628","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/meditcom58224.2023.10266628","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)","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/A5069831147","display_name":"Juan Augusto Maya","orcid":"https://orcid.org/0000-0002-5072-343X"},"institutions":[{"id":"https://openalex.org/I4210166741","display_name":"University of Klagenfurt","ror":"https://ror.org/05q9m0937","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210166741"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Juan Augusto Maya","raw_affiliation_strings":["University of Klagenfurt,Ubiquitous Sensing Lab,Klagenfurt,Austria","Ubiquitous Sensing Lab, University of Klagenfurt, Klagenfurt, Austria"],"affiliations":[{"raw_affiliation_string":"University of Klagenfurt,Ubiquitous Sensing Lab,Klagenfurt,Austria","institution_ids":["https://openalex.org/I4210166741"]},{"raw_affiliation_string":"Ubiquitous Sensing Lab, University of Klagenfurt, Klagenfurt, Austria","institution_ids":["https://openalex.org/I4210166741"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035529329","display_name":"Leonardo Rey Vega","orcid":"https://orcid.org/0000-0002-5578-0521"},"institutions":[{"id":"https://openalex.org/I24354313","display_name":"University of Buenos Aires","ror":"https://ror.org/0081fs513","country_code":"AR","type":"education","lineage":["https://openalex.org/I24354313"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Leonardo Rey Vega","raw_affiliation_strings":["University of Buenos Aires,School of Engineering,Buenos Aires,Argentina","School of Engineering, University of Buenos Aires, Buenos Aires, Argentina"],"affiliations":[{"raw_affiliation_string":"University of Buenos Aires,School of Engineering,Buenos Aires,Argentina","institution_ids":["https://openalex.org/I24354313"]},{"raw_affiliation_string":"School of Engineering, University of Buenos Aires, Buenos Aires, Argentina","institution_ids":["https://openalex.org/I24354313"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046459259","display_name":"Andrea M. Tonello","orcid":"https://orcid.org/0000-0002-9873-2407"},"institutions":[{"id":"https://openalex.org/I4210166741","display_name":"University of Klagenfurt","ror":"https://ror.org/05q9m0937","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210166741"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Andrea M. Tonello","raw_affiliation_strings":["University of Klagenfurt,Institute of Networked and Embedded Systems,Klagenfurt,Austria","Institute of Networked and Embedded Systems, University of Klagenfurt, Klagenfurt, Austria"],"affiliations":[{"raw_affiliation_string":"University of Klagenfurt,Institute of Networked and Embedded Systems,Klagenfurt,Austria","institution_ids":["https://openalex.org/I4210166741"]},{"raw_affiliation_string":"Institute of Networked and Embedded Systems, University of Klagenfurt, Klagenfurt, Austria","institution_ids":["https://openalex.org/I4210166741"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5069831147"],"corresponding_institution_ids":["https://openalex.org/I4210166741"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14758549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"352","last_page":"357"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11720","display_name":"Probability and Risk Models","score":0.9782000184059143,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.7786858081817627},{"id":"https://openalex.org/keywords/fusion-center","display_name":"Fusion center","score":0.6252537369728088},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.49805665016174316},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4847697615623474},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.47334957122802734},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.46962809562683105},{"id":"https://openalex.org/keywords/test-statistic","display_name":"Test statistic","score":0.46237608790397644},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4514072835445404},{"id":"https://openalex.org/keywords/sufficient-statistic","display_name":"Sufficient statistic","score":0.41250336170196533},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4117882251739502},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4117244780063629},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.38925087451934814},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36696141958236694},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.30886510014533997},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.26254650950431824},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1433902084827423}],"concepts":[{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.7786858081817627},{"id":"https://openalex.org/C2781234732","wikidata":"https://www.wikidata.org/wiki/Q943505","display_name":"Fusion center","level":4,"score":0.6252537369728088},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.49805665016174316},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4847697615623474},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.47334957122802734},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.46962809562683105},{"id":"https://openalex.org/C169857963","wikidata":"https://www.wikidata.org/wiki/Q1461038","display_name":"Test statistic","level":3,"score":0.46237608790397644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4514072835445404},{"id":"https://openalex.org/C178197554","wikidata":"https://www.wikidata.org/wiki/Q1099110","display_name":"Sufficient statistic","level":2,"score":0.41250336170196533},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4117882251739502},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4117244780063629},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.38925087451934814},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36696141958236694},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.30886510014533997},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.26254650950431824},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1433902084827423},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/meditcom58224.2023.10266628","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/meditcom58224.2023.10266628","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320318209","display_name":"Silicon Austria Labs","ror":"https://ror.org/03b1qgn79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1995453571","https://openalex.org/W2005660297","https://openalex.org/W2088801740","https://openalex.org/W2116972936","https://openalex.org/W2164701487","https://openalex.org/W2165800172","https://openalex.org/W2171402290","https://openalex.org/W2987325717","https://openalex.org/W3008672147","https://openalex.org/W3017564100","https://openalex.org/W3026290994","https://openalex.org/W3128947043","https://openalex.org/W3162490357","https://openalex.org/W4388642307","https://openalex.org/W4389610093","https://openalex.org/W6846742735"],"related_works":["https://openalex.org/W2073148077","https://openalex.org/W2911309053","https://openalex.org/W3034370451","https://openalex.org/W1992932675","https://openalex.org/W2071792881","https://openalex.org/W3213182273","https://openalex.org/W2909288057","https://openalex.org/W2584466131","https://openalex.org/W2168908332","https://openalex.org/W2031443741"],"abstract_inverted_index":{"We":[0,46],"consider":[1],"the":[2,39,48,72,78,81,88,92,97,100,105,124,134,139,147,151,156,164,183,188,192,198,202,206,222],"problem":[3],"of":[4,7,38,80,99,107,133,138,150,158,191],"distributed":[5,15,130],"detection":[6,199],"a":[8,12,22,29,33,52,143,210],"radio":[9,49,73],"source":[10,40,50,74],"emitting":[11],"signal.":[13],"Geographically":[14],"sensor":[16,108],"nodes":[17],"obtain":[18],"energy":[19],"measurements,":[20,61,140],"compute":[21],"local":[23],"statistic,":[24],"and":[25,55,162,214,235],"transmit":[26],"them":[27],"to":[28,36,111,179,182,221],"fusion":[30],"center,":[31],"where":[32,146],"decision":[34],"regarding":[35],"state":[37],"(on":[41],"or":[42],"off)":[43],"is":[44,75,126,153,167,177],"made.":[45],"model":[47],"as":[51,123,219],"stochastic":[53],"signal":[54],"deal":[56],"with":[57,232],"spatially":[58],"statistically":[59,136,189],"dependent":[60],"whose":[62],"probability":[63],"density":[64],"function":[65],"(PDF)":[66],"has":[67,194,209],"unknown":[68,93],"positive":[69,89],"parameters":[70,95],"when":[71],"active.":[76],"Under":[77],"framework":[79],"Generalized":[82],"Likelihood":[83],"Ratio":[84],"Test":[85],"(GLRT)":[86],"theory,":[87],"constraint":[90],"on":[91,197],"multidimensional":[94],"makes":[96],"computation":[98,234],"GLRT":[101,125],"asymptotic":[102,120,175,203],"performance":[103,176,200],"(when":[104],"amount":[106],"measurements":[109,152,193],"tends":[110],"infinity)":[112],"more":[113],"involved.":[114],"Nevertheless,":[115],"we":[116,141],"analytically":[117],"characterize":[118],"its":[119,159],"performance.":[121],"Moreover,":[122],"not":[127],"amenable":[128],"for":[129,170,228],"settings":[131],"because":[132],"spatial":[135],"dependence":[137,166,190],"study":[142],"GLRT-like":[144,207],"test":[145],"joint":[148],"PDF":[149],"substituted":[154],"by":[155],"product":[157],"marginal":[160],"PDFs,":[161],"therefore,":[163],"statistical":[165],"completely":[168],"discarded":[169],"building":[171],"this":[172],"test.":[173],"Its":[174],"proved":[178],"be":[180],"identical":[181],"original":[184],"GLRT,":[185,223],"showing":[186],"that":[187],"no":[195],"impact":[196],"in":[201],"scenario.":[204],"Furthermore,":[205],"algorithm":[208],"low":[211,216],"computational":[212],"complexity":[213],"demands":[215],"communication":[217,236],"resources,":[218],"compared":[220],"which":[224],"make":[225],"it":[226],"suitable":[227],"Wireless":[229],"Sensor":[230],"Networks":[231],"scarce":[233],"resources.":[237]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
