{"id":"https://openalex.org/W2998239342","doi":"https://doi.org/10.1109/icct46805.2019.8947316","title":"A Spectrum Sensing Algorithm Based on Linear Discriminant Analysis and Extreme Gradient Boosting in Cognitive Radio","display_name":"A Spectrum Sensing Algorithm Based on Linear Discriminant Analysis and Extreme Gradient Boosting in Cognitive Radio","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2998239342","doi":"https://doi.org/10.1109/icct46805.2019.8947316","mag":"2998239342"},"language":"en","primary_location":{"id":"doi:10.1109/icct46805.2019.8947316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct46805.2019.8947316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","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/A5100400800","display_name":"Ran Chen","orcid":"https://orcid.org/0000-0002-2770-4070"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ran Chen","raw_affiliation_strings":["School of Information & Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information & Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043356020","display_name":"Yubai Li","orcid":"https://orcid.org/0000-0003-0507-3201"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubai Li","raw_affiliation_strings":["School of Information & Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information & Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100400800"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.20929256,"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":"762","last_page":"769"},"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9807999730110168,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.6737004518508911},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6431294679641724},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.5817702412605286},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5715374946594238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5377184748649597},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5292519927024841},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5203834772109985},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.49492377042770386},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.42541196942329407},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.400746613740921},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.3102070689201355},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12786728143692017}],"concepts":[{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.6737004518508911},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6431294679641724},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.5817702412605286},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5715374946594238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5377184748649597},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5292519927024841},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5203834772109985},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.49492377042770386},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.42541196942329407},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.400746613740921},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.3102070689201355},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12786728143692017}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icct46805.2019.8947316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct46805.2019.8947316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7599999904632568,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W1925095223","https://openalex.org/W1982436641","https://openalex.org/W2021167230","https://openalex.org/W2065424480","https://openalex.org/W2090181954","https://openalex.org/W2101734002","https://openalex.org/W2101840010","https://openalex.org/W2150796457","https://openalex.org/W2295598076","https://openalex.org/W2325359412","https://openalex.org/W3150751370"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W1538046993","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561"],"abstract_inverted_index":{"Spectrum":[0],"sensing":[1,34,110],"is":[2,47,80,112],"one":[3],"of":[4,18,60,98],"the":[5,15,50,57,61,64,72,77,84,89,95,99,105,108,115,128],"key":[6],"technologies":[7],"in":[8,25],"cognitive":[9],"radio,":[10],"which":[11,87],"can":[12,67],"greatly":[13],"improve":[14],"utilization":[16],"rate":[17],"spectrum":[19,24,33,59,74,109],"resources":[20],"by":[21,70,114],"detecting":[22],"idle":[23],"real":[26],"time.":[27],"In":[28],"this":[29],"paper,":[30],"a":[31],"new":[32],"algorithm":[35,79,130,143],"based":[36,103],"on":[37,104],"LDA":[38,78],"(Linear":[39],"discriminant":[40],"analysis)":[41],"and":[42,63,93,135,141],"XGBoost":[43,116],"(Extreme":[44],"gradient":[45],"boosting)":[46],"proposed.":[48],"Firstly,":[49],"three-dimensional":[51],"eigenvectors":[52],"are":[53],"extracted":[54],"according":[55],"to":[56,82],"cyclic":[58,73],"signal,":[62],"anti-noise":[65],"performance":[66,134],"be":[68],"improved":[69],"using":[71],"features.":[75],"Then":[76],"used":[81],"reduce":[83],"feature":[85,91],"dimension,":[86],"reduces":[88],"similar":[90],"redundancy":[92],"improves":[94],"training":[96,137],"speed":[97,138],"subsequent":[100],"algorithm.":[101,117],"Finally,":[102],"transformed":[106],"samples,":[107],"model":[111],"trained":[113],"The":[118],"experimental":[119],"results":[120],"show":[121],"that":[122],"for":[123],"different":[124],"primary":[125],"user":[126],"signals,":[127],"proposed":[129],"has":[131],"better":[132],"detection":[133],"faster":[136],"than":[139],"SVM":[140],"AdaBoost":[142],"at":[144],"low":[145],"SNR.":[146]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
