{"id":"https://openalex.org/W3046540519","doi":"https://doi.org/10.1109/lsp.2020.3013529","title":"Dynamic Markov Chain Monte Carlo-Based Spectrum Sensing","display_name":"Dynamic Markov Chain Monte Carlo-Based Spectrum Sensing","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3046540519","doi":"https://doi.org/10.1109/lsp.2020.3013529","mag":"3046540519"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.3013529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3013529","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.ucl.ac.uk/10112048/1/Dynamic%20Markov%20Chain%20Monte%20Carlo-Based%20Spectrum%20Sensing.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100401162","display_name":"Zheng Wang","orcid":"https://orcid.org/0000-0003-3528-558X"},"institutions":[{"id":"https://openalex.org/I4391767685","display_name":"State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System","ror":"https://ror.org/012ajw921","country_code":null,"type":"facility","lineage":["https://openalex.org/I170215575","https://openalex.org/I4391767685"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]},{"id":"https://openalex.org/I890469752","display_name":"Ministry of Industry and Information Technology","ror":"https://ror.org/0385nmy68","country_code":"CN","type":"government","lineage":["https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zheng Wang","raw_affiliation_strings":["Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space (Nanjing Univ. Aeronaut. Astronaut.), Ministry of Industry and Information Technology, Nanjing, China","National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, CEMEE, Luoyang, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space (Nanjing Univ. Aeronaut. Astronaut.), Ministry of Industry and Information Technology, Nanjing, China","institution_ids":["https://openalex.org/I890469752"]},{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, CEMEE, Luoyang, China","institution_ids":["https://openalex.org/I4391767685"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102724843","display_name":"Ling Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Liu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101786299","display_name":"Kezhi Li","orcid":"https://orcid.org/0000-0003-3073-3128"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kezhi Li","raw_affiliation_strings":["Institute of Health Informatics, University College London, London, U.K"],"affiliations":[{"raw_affiliation_string":"Institute of Health Informatics, University College London, London, U.K","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100401162"],"corresponding_institution_ids":["https://openalex.org/I4391767685","https://openalex.org/I76569877","https://openalex.org/I890469752"],"apc_list":null,"apc_paid":null,"fwci":1.1318,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80258615,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"27","issue":null,"first_page":"1380","last_page":"1384"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9983000159263611,"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/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.8789898753166199},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.7111539840698242},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6513643860816956},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6319127082824707},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6200899481773376},{"id":"https://openalex.org/keywords/rejection-sampling","display_name":"Rejection sampling","score":0.5784090757369995},{"id":"https://openalex.org/keywords/slice-sampling","display_name":"Slice sampling","score":0.555939793586731},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5436500906944275},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5208509564399719},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5149860978126526},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4960874021053314},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.4918959140777588},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.4155648350715637},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.41481178998947144},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.38474419713020325},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3683573305606842},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23414936661720276},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18882498145103455},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16688385605812073},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.13233473896980286},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12110009789466858}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.8789898753166199},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.7111539840698242},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6513643860816956},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6319127082824707},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6200899481773376},{"id":"https://openalex.org/C187192777","wikidata":"https://www.wikidata.org/wiki/Q381699","display_name":"Rejection sampling","level":5,"score":0.5784090757369995},{"id":"https://openalex.org/C170593435","wikidata":"https://www.wikidata.org/wiki/Q4128565","display_name":"Slice sampling","level":4,"score":0.555939793586731},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5436500906944275},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5208509564399719},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5149860978126526},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4960874021053314},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.4918959140777588},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.4155648350715637},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.41481178998947144},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.38474419713020325},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3683573305606842},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23414936661720276},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18882498145103455},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16688385605812073},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.13233473896980286},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12110009789466858},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2020.3013529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3013529","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10112048","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10112048/","pdf_url":"https://discovery.ucl.ac.uk/10112048/1/Dynamic%20Markov%20Chain%20Monte%20Carlo-Based%20Spectrum%20Sensing.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   IEEE Signal Processing Letters , 27    pp. 1380-1384.   (2020)      ","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10112048","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10112048/","pdf_url":"https://discovery.ucl.ac.uk/10112048/1/Dynamic%20Markov%20Chain%20Monte%20Carlo-Based%20Spectrum%20Sensing.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   IEEE Signal Processing Letters , 27    pp. 1380-1384.   (2020)      ","raw_type":"Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3277593382","display_name":null,"funder_award_id":"61801216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G801768937","display_name":null,"funder_award_id":"BK20180420","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3046540519.pdf","grobid_xml":"https://content.openalex.org/works/W3046540519.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1600293573","https://openalex.org/W1992167710","https://openalex.org/W2005548917","https://openalex.org/W2036002803","https://openalex.org/W2144688966","https://openalex.org/W2163588941","https://openalex.org/W2322798001","https://openalex.org/W2551956255","https://openalex.org/W2787245337","https://openalex.org/W2883749581","https://openalex.org/W2962810704","https://openalex.org/W2962985151"],"related_works":["https://openalex.org/W4295750535","https://openalex.org/W3097509027","https://openalex.org/W105676162","https://openalex.org/W2783865284","https://openalex.org/W2592308920","https://openalex.org/W2059147320","https://openalex.org/W3082406322","https://openalex.org/W2122865681","https://openalex.org/W4248662691","https://openalex.org/W1964820882"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"a":[3],"random":[4],"sampling":[5,40,60,84],"strategy":[6],"is":[7,61,71],"proposed":[8,26,82],"for":[9,36],"the":[10,32,42,59,65,68,78,81],"non-cooperative":[11],"spectrum":[12],"sensing":[13,38,88],"to":[14],"improve":[15],"its":[16],"performance":[17,89],"and":[18,64,90],"efficiency":[19],"in":[20,47,73,86],"cognitive":[21],"radio":[22],"(CR)":[23],"networks.":[24],"The":[25,55],"refined":[27],"Metropolis-Hastings":[28],"(RMH)":[29],"algorithm":[30,85],"generates":[31],"desired":[33],"channel":[34,44],"sequence":[35],"fine":[37],"by":[39],"from":[41],"approximated":[43],"availability":[45],"distributions":[46],"an":[48],"Markov":[49,69],"chain":[50,70],"Monte":[51],"Carlo":[52],"(MCMC)":[53],"way.":[54],"proposal":[56],"distribution":[57],"during":[58],"fully":[62],"exploited":[63],"convergence":[66],"of":[67,80],"studied":[72],"detail,":[74],"which":[75],"theoretically":[76],"demonstrate":[77],"superiorities":[79],"RMH":[83],"both":[87],"efficiency.":[91]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
