{"id":"https://openalex.org/W4205325705","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660470","title":"A Spectrum Sensing Method Based on CNN-LSTM Deep Neural Network","display_name":"A Spectrum Sensing Method Based on CNN-LSTM Deep Neural Network","publication_year":2021,"publication_date":"2021-11-17","ids":{"openalex":"https://openalex.org/W4205325705","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660470"},"language":"en","primary_location":{"id":"doi:10.1109/ic-nidc54101.2021.9660470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660470","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","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/A5056212977","display_name":"Shujian Zhang","orcid":"https://orcid.org/0000-0003-3216-722X"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shujian Zhang","raw_affiliation_strings":["Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Beijing, China","School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]},{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050256911","display_name":"Zhan Xu","orcid":"https://orcid.org/0000-0001-5301-9600"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhan Xu","raw_affiliation_strings":["Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Beijing, China","School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]},{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102117037","display_name":"Lu Tian","orcid":"https://orcid.org/0000-0001-9265-0040"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Tian","raw_affiliation_strings":["Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Beijing, China","School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]},{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064430071","display_name":"Xiaolong Yang","orcid":"https://orcid.org/0000-0001-6193-2926"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Yang","raw_affiliation_strings":["Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Beijing, China","School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]},{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056212977"],"corresponding_institution_ids":["https://openalex.org/I78675632"],"apc_list":null,"apc_paid":null,"fwci":0.308,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.41677034,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"186","last_page":"190"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9969000220298767,"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":0.9945999979972839,"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/spectrogram","display_name":"Spectrogram","score":0.8453099727630615},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7950800657272339},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6602675914764404},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6156560182571411},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.604851245880127},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5950608253479004},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5728821754455566},{"id":"https://openalex.org/keywords/timestamp","display_name":"Timestamp","score":0.5489372611045837},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.5039898753166199},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4776916801929474},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.4423469007015228},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.43248865008354187},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42934104800224304},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.165929913520813},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.12364104390144348},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1004854142665863},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.08324548602104187}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.8453099727630615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7950800657272339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6602675914764404},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6156560182571411},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.604851245880127},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5950608253479004},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5728821754455566},{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.5489372611045837},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5039898753166199},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4776916801929474},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.4423469007015228},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.43248865008354187},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42934104800224304},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.165929913520813},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.12364104390144348},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1004854142665863},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.08324548602104187},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","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/ic-nidc54101.2021.9660470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660470","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G2882451678","display_name":null,"funder_award_id":"2020YFC1511701","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2065424480","https://openalex.org/W2155999145","https://openalex.org/W2167973602","https://openalex.org/W2579790822","https://openalex.org/W2908993293","https://openalex.org/W3035433808","https://openalex.org/W3039695658"],"related_works":["https://openalex.org/W1889291648","https://openalex.org/W2533590149","https://openalex.org/W335396218","https://openalex.org/W1504214173","https://openalex.org/W1600447354","https://openalex.org/W1589126043","https://openalex.org/W2035480840","https://openalex.org/W2602361891","https://openalex.org/W2107964963","https://openalex.org/W2149263408"],"abstract_inverted_index":{"Spectrum":[0],"sensing":[1,38],"can":[2,121],"effectively":[3],"improve":[4],"the":[5,15,46,52,56,66,70,83,96,102,108,116,139],"low":[6,142],"utilization":[7],"of":[8,14,18,51,107,125,135,141],"spectrum":[9,37,80],"resources":[10],"and":[11,30,81,104],"is":[12,63],"one":[13],"crucial":[16],"components":[17],"cognitive":[19],"radio":[20],"networks.":[21],"This":[22],"paper":[23,120],"proposes":[24],"a":[25,75,78,123,132],"Convolutional":[26],"Neural":[27],"Network":[28],"(CNN)":[29],"Long":[31],"Short-Term":[32],"Memory":[33],"(LSTM)":[34],"network":[35,93],"cascaded":[36],"model.":[39],"The":[40,91,111],"model":[41,94],"uses":[42],"CNN":[43],"to":[44,65,69,86],"analyze":[45],"Short-Time":[47],"Fourier":[48],"transform":[49],"spectrogram":[50],"blind":[53,109],"signal.":[54,110],"Then":[55],"generated":[57],"feature":[58,61],"vector":[59],"or":[60],"map":[62],"passed":[64],"LSTM":[67],"according":[68],"timestamp.":[71],"Finally,":[72],"it":[73],"detects":[74],"signal":[76,84],"in":[77,118],"specific":[79],"classifies":[82],"type":[85],"identify":[87],"multiple":[88],"signals":[89,126],"accurately.":[90],"neural":[92],"improves":[95],"detection":[97,129],"probability":[98,130],"by":[99],"simultaneously":[100],"acquiring":[101],"spatial":[103],"temporal":[105],"characteristics":[106],"experimental":[112],"results":[113],"show":[114],"that":[115],"method":[117],"this":[119],"detect":[122],"variety":[124],"with":[127],"higher":[128],"within":[131],"wide":[133],"range":[134],"SNR,":[136],"especially":[137],"under":[138],"condition":[140],"SNR.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}