{"id":"https://openalex.org/W4411576272","doi":"https://doi.org/10.4108/eetsis.9552","title":"A Cholesky decomposition and fusion clustering based spectrum sensing method","display_name":"A Cholesky decomposition and fusion clustering based spectrum sensing method","publication_year":2025,"publication_date":"2025-06-24","ids":{"openalex":"https://openalex.org/W4411576272","doi":"https://doi.org/10.4108/eetsis.9552"},"language":"en","primary_location":{"id":"doi:10.4108/eetsis.9552","is_oa":true,"landing_page_url":"https://doi.org/10.4108/eetsis.9552","pdf_url":"https://publications.eai.eu/index.php/sis/article/download/9552/3618","source":{"id":"https://openalex.org/S4210240886","display_name":"ICST Transactions on Scalable Information Systems","issn_l":"2032-9407","issn":["2032-9407"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321145","host_organization_name":"European Alliance for Innovation","host_organization_lineage":["https://openalex.org/P4310321145"],"host_organization_lineage_names":["European Alliance for Innovation"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICST Transactions on Scalable Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://publications.eai.eu/index.php/sis/article/download/9552/3618","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077766428","display_name":"Jian Hua Li","orcid":"https://orcid.org/0000-0002-6799-7410"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Li","raw_affiliation_strings":["Heilongjiang University"],"affiliations":[{"raw_affiliation_string":"Heilongjiang University","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100387753","display_name":"Yue Li","orcid":"https://orcid.org/0000-0001-9562-3136"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Li","raw_affiliation_strings":["Heilongjiang University"],"affiliations":[{"raw_affiliation_string":"Heilongjiang University","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102636467","display_name":"Xinpei Zhao","orcid":"https://orcid.org/0009-0000-6597-7582"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinpei Zhao","raw_affiliation_strings":["Heilongjiang University"],"affiliations":[{"raw_affiliation_string":"Heilongjiang University","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102023780","display_name":"Xiaoxu Chen","orcid":"https://orcid.org/0000-0003-3629-6109"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxu Chen","raw_affiliation_strings":["Heilongjiang University"],"affiliations":[{"raw_affiliation_string":"Heilongjiang University","institution_ids":["https://openalex.org/I55022517"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5077766428"],"corresponding_institution_ids":["https://openalex.org/I55022517"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16453542,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","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/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","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/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9970999956130981,"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/cholesky-decomposition","display_name":"Cholesky decomposition","score":0.9285635948181152},{"id":"https://openalex.org/keywords/spectrum","display_name":"Spectrum (functional analysis)","score":0.6052534580230713},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5679464340209961},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.530998945236206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5004782676696777},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4878940284252167},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4095602333545685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39150387048721313},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.20925688743591309},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15815261006355286},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.10472607612609863},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.06239566206932068}],"concepts":[{"id":"https://openalex.org/C34727166","wikidata":"https://www.wikidata.org/wiki/Q515375","display_name":"Cholesky decomposition","level":3,"score":0.9285635948181152},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.6052534580230713},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5679464340209961},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.530998945236206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5004782676696777},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4878940284252167},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4095602333545685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39150387048721313},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.20925688743591309},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15815261006355286},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.10472607612609863},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.06239566206932068},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4108/eetsis.9552","is_oa":true,"landing_page_url":"https://doi.org/10.4108/eetsis.9552","pdf_url":"https://publications.eai.eu/index.php/sis/article/download/9552/3618","source":{"id":"https://openalex.org/S4210240886","display_name":"ICST Transactions on Scalable Information Systems","issn_l":"2032-9407","issn":["2032-9407"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321145","host_organization_name":"European Alliance for Innovation","host_organization_lineage":["https://openalex.org/P4310321145"],"host_organization_lineage_names":["European Alliance for Innovation"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICST Transactions on Scalable Information Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.4108/eetsis.9552","is_oa":true,"landing_page_url":"https://doi.org/10.4108/eetsis.9552","pdf_url":"https://publications.eai.eu/index.php/sis/article/download/9552/3618","source":{"id":"https://openalex.org/S4210240886","display_name":"ICST Transactions on Scalable Information Systems","issn_l":"2032-9407","issn":["2032-9407"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321145","host_organization_name":"European Alliance for Innovation","host_organization_lineage":["https://openalex.org/P4310321145"],"host_organization_lineage_names":["European Alliance for Innovation"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICST Transactions on Scalable Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411576272.pdf","grobid_xml":"https://content.openalex.org/works/W4411576272.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1517733625","https://openalex.org/W1592113329","https://openalex.org/W2013146406","https://openalex.org/W2058074751","https://openalex.org/W2091005538","https://openalex.org/W2122226128","https://openalex.org/W2129510251","https://openalex.org/W2136816673","https://openalex.org/W2206059354","https://openalex.org/W2292235123","https://openalex.org/W2294942837","https://openalex.org/W2520664327","https://openalex.org/W2556143762","https://openalex.org/W2734810207","https://openalex.org/W2766522006","https://openalex.org/W2790000061","https://openalex.org/W2797971294","https://openalex.org/W2914662441","https://openalex.org/W2957615201"],"related_works":["https://openalex.org/W2403987929","https://openalex.org/W2039814159","https://openalex.org/W2374847384","https://openalex.org/W2063512590","https://openalex.org/W2107649022","https://openalex.org/W2356488190","https://openalex.org/W2966537581","https://openalex.org/W2079508979","https://openalex.org/W1970284238","https://openalex.org/W604331851"],"abstract_inverted_index":{"Spectrum":[0],"sensing":[1,30,153],"is":[2,12,24,62,74,96,103],"a":[3,25,44],"key":[4],"technology":[5],"to":[6,27,85,105,155],"detect":[7],"unused":[8],"frequency":[9],"bands,":[10],"and":[11,18,51,69,71,82,110,120,141],"widely":[13],"applied":[14],"in":[15],"spectrum":[16,152],"sharing":[17],"dynamic":[19],"channel":[20],"allocation.":[21],"However,":[22],"it":[23],"challenge":[26],"provide":[28],"high":[29],"accuracy":[31],"under":[32],"low":[33],"signal-to-noise-ratio":[34],"(SNR)":[35],"environments.":[36],"To":[37],"address":[38],"this":[39,41],"issue,":[40],"paper":[42],"proposes":[43],"novel":[45],"method":[46,134],"based":[47],"on":[48,76],"feature":[49,89,108],"extraction":[50],"fusion":[52,93],"clustering.":[53,127],"First,":[54],"the":[55,59,77,92,99,107,111,132,136,143,149],"sampling":[56],"matrix":[57],"of":[58,80,114,139,151],"received":[60],"signal":[61],"decomposed":[63],"into":[64],"two":[65],"orthogonal":[66],"components":[67,84],"I":[68,81],"Q,":[70],"Cholesky":[72],"decomposition":[73],"performed":[75,104],"covariance":[78,121],"matrices":[79],"Q":[83],"extract":[86],"their":[87],"two-dimensional":[88],"vectors.":[90],"Then,":[91],"clustering":[94,101],"algorithm":[95,102],"proposed,":[97],"where":[98],"GMM":[100,140],"classify":[106],"vectors,":[109],"initial":[112],"parameters":[113],"GMM,":[115],"such":[116],"as":[117],"centroids,":[118],"weights":[119],"matrices,":[122],"are":[123],"generated":[124],"by":[125],"K-means":[126],"Simulation":[128],"results":[129],"show":[130],"that":[131],"proposed":[133],"accelerates":[135],"convergence":[137],"speed":[138],"improves":[142],"classification":[144],"accuracy.":[145],"It":[146],"effectively":[147],"enhances":[148],"performance":[150],"compared":[154],"other":[156],"mainstream":[157],"methods.":[158]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}