{"id":"https://openalex.org/W4290993855","doi":"https://doi.org/10.1109/tsp.2022.3198186","title":"Approaching Sub-Nyquist Boundary: Optimized Compressed Spectrum Sensing Based on Multicoset Sampler for Multiband Signal","display_name":"Approaching Sub-Nyquist Boundary: Optimized Compressed Spectrum Sensing Based on Multicoset Sampler for Multiband Signal","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4290993855","doi":"https://doi.org/10.1109/tsp.2022.3198186"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2022.3198186","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3198186","pdf_url":"https://ieeexplore.ieee.org/ielx7/78/4359509/09855237.pdf","source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/78/4359509/09855237.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039634724","display_name":"Zihang Song","orcid":null},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Zihang Song","raw_affiliation_strings":["Institute for Communication Systems, University of Surrey, Guildford, U.K"],"affiliations":[{"raw_affiliation_string":"Institute for Communication Systems, University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101744546","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0002-1756-5361"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yang","raw_affiliation_strings":["School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100399277","display_name":"Han Zhang","orcid":"https://orcid.org/0000-0002-0171-0819"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Han Zhang","raw_affiliation_strings":["Institute for Communication Systems, University of Surrey, Guildford, U.K"],"affiliations":[{"raw_affiliation_string":"Institute for Communication Systems, University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075109962","display_name":"Yue Gao","orcid":"https://orcid.org/0000-0001-6502-9910"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yue Gao","raw_affiliation_strings":["Institute for Communication Systems, University of Surrey, Guildford, U.K"],"affiliations":[{"raw_affiliation_string":"Institute for Communication Systems, University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5039634724"],"corresponding_institution_ids":["https://openalex.org/I28290843"],"apc_list":null,"apc_paid":null,"fwci":3.4884,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.93395654,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"70","issue":null,"first_page":"4225","last_page":"4238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.793390154838562},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.7099178433418274},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6467936038970947},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6050134897232056},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5664228200912476},{"id":"https://openalex.org/keywords/nyquist-rate","display_name":"Nyquist rate","score":0.5566455125808716},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5062860250473022},{"id":"https://openalex.org/keywords/nyquist\u2013shannon-sampling-theorem","display_name":"Nyquist\u2013Shannon sampling theorem","score":0.4950332045555115},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.4220905005931854},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41588079929351807},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41146230697631836},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3830644190311432},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3388761878013611},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3198533058166504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2211395502090454},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.14156055450439453},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.13531750440597534},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1159147322177887}],"concepts":[{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.793390154838562},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.7099178433418274},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6467936038970947},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6050134897232056},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5664228200912476},{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.5566455125808716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5062860250473022},{"id":"https://openalex.org/C288623","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Nyquist\u2013Shannon sampling theorem","level":2,"score":0.4950332045555115},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.4220905005931854},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41588079929351807},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41146230697631836},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3830644190311432},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3388761878013611},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3198533058166504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2211395502090454},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.14156055450439453},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.13531750440597534},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1159147322177887},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2022.3198186","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3198186","pdf_url":"https://ieeexplore.ieee.org/ielx7/78/4359509/09855237.pdf","source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tsp.2022.3198186","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3198186","pdf_url":"https://ieeexplore.ieee.org/ielx7/78/4359509/09855237.pdf","source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1934935867","display_name":null,"funder_award_id":"Engineering and Physical Sciences R","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3145248118","display_name":null,"funder_award_id":"EP/R00711X/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G4646286159","display_name":"GBSense: GHz Bandwidth Sensing from Smart Antennas to Sub-Nyquist Signal Processing","funder_award_id":"EP/R00711X/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4290993855.pdf","grobid_xml":"https://content.openalex.org/works/W4290993855.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W143004564","https://openalex.org/W1993784401","https://openalex.org/W1996692478","https://openalex.org/W2014780099","https://openalex.org/W2027163759","https://openalex.org/W2040367593","https://openalex.org/W2046612908","https://openalex.org/W2061158652","https://openalex.org/W2078204800","https://openalex.org/W2099641086","https://openalex.org/W2110160451","https://openalex.org/W2114129195","https://openalex.org/W2123629701","https://openalex.org/W2127271355","https://openalex.org/W2129131372","https://openalex.org/W2135115617","https://openalex.org/W2135338342","https://openalex.org/W2138548210","https://openalex.org/W2149406951","https://openalex.org/W2151693816","https://openalex.org/W2153620960","https://openalex.org/W2154332973","https://openalex.org/W2160979406","https://openalex.org/W2162409952","https://openalex.org/W2164452299","https://openalex.org/W2169707415","https://openalex.org/W2197633902","https://openalex.org/W2289917018","https://openalex.org/W2746433858","https://openalex.org/W2787743626","https://openalex.org/W2797136165","https://openalex.org/W2979659267","https://openalex.org/W2980068825","https://openalex.org/W3104922853","https://openalex.org/W3152497848","https://openalex.org/W3162803139","https://openalex.org/W3166633225","https://openalex.org/W3173535513","https://openalex.org/W4211007270","https://openalex.org/W4225699678","https://openalex.org/W4252265035","https://openalex.org/W6631898046"],"related_works":["https://openalex.org/W2999872239","https://openalex.org/W2210983845","https://openalex.org/W2054047433","https://openalex.org/W2381127329","https://openalex.org/W3103056594","https://openalex.org/W2536408609","https://openalex.org/W2119250743","https://openalex.org/W2545081564","https://openalex.org/W2618908398","https://openalex.org/W4245974431"],"abstract_inverted_index":{"Compressed":[0],"spectrum":[1,13,62,108,128,150],"sensing":[2,134],"naturally":[3],"pursues":[4],"the":[5,29,38,50,57,89,104,107,127,133,139,142,148,153,176,196,201,207,217],"use":[6],"of":[7,23,126,141,156,200],"fewer":[8],"sampling":[9,25,52,69,114,209,219],"resources":[10],"to":[11,27,35,102,120,131,168,175,194,211],"achieve":[12],"support":[14,109,129],"reconstruction":[15,63,73,87,111,130,214],"and":[16,71,78,144,198],"signal":[17,31,94,143],"recovery.":[18],"The":[19],"theoretical":[20],"lower":[21],"boundary":[22],"averaging":[24],"rate":[26,125,173],"recover":[28],"multiband":[30],"has":[32],"been":[33],"proved":[34],"be":[36],"twice":[37],"Landau":[39],"rate.":[40],"However,":[41],"it":[42],"is":[43,100,118,215],"still":[44],"unreachable":[45],"in":[46,106,147],"practice.":[47],"Based":[48],"on":[49,60,152,187],"multicoset":[51],"architecture,":[53],"this":[54],"paper":[55],"analyzes":[56],"influencing":[58],"factors":[59],"perfect":[61,213],"from":[64],"three":[65],"aspects:":[66],"data":[67],"model,":[68,95],"pattern":[70,115],"greedy":[72],"algorithms,":[74],"for":[75,88,181],"which":[76],"practical":[77],"feasible":[79],"optimization":[80],"schemes":[81],"are":[82,191],"proposed.":[83],"To":[84],"reduce":[85],"redundant":[86],"multiple":[90],"measurement":[91],"vectors":[92],"(MMV)":[93],"a":[96,122,162,170],"block":[97],"MMV":[98],"model":[99,155],"proposed":[101,119,161,202],"improve":[103],"accuracy":[105],"set":[110,178],"process.":[112],"A":[113],"selection":[116],"algorithm":[117,167],"ensure":[121,212],"higher":[123],"success":[124],"optimize":[132],"matrix.":[135],"We":[136,159],"also":[137],"deduced":[138],"representation":[140],"noise":[145],"energy":[146],"reconstructed":[149],"based":[151],"mathematical":[154],"compressed":[157],"sensing.":[158],"thus":[160],"non-orthogonal":[163],"double-threshold":[164],"matching":[165,182],"pursuit":[166,183],"avoid":[169],"high":[171],"false-alarm":[172],"due":[174],"manually":[177],"converging":[179],"conditions":[180],"algorithms.":[184],"Numerical":[185],"experiments":[186],"real-world":[188],"wideband":[189],"signals":[190],"carried":[192],"out":[193],"demonstrate":[195],"feasibility":[197],"advantages":[199],"approaches.":[203],"With":[204],"integrated":[205],"optimization,":[206],"required":[208],"density":[210],"approaching":[216],"sub-Nyquist":[218],"boundary.":[220]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}