{"id":"https://openalex.org/W2169441574","doi":"https://doi.org/10.1186/1687-1499-2013-47","title":"Spectrum efficiency of nested sparse sampling and coprime sampling","display_name":"Spectrum efficiency of nested sparse sampling and coprime sampling","publication_year":2013,"publication_date":"2013-02-22","ids":{"openalex":"https://openalex.org/W2169441574","doi":"https://doi.org/10.1186/1687-1499-2013-47","mag":"2169441574"},"language":"en","primary_location":{"id":"doi:10.1186/1687-1499-2013-47","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-1499-2013-47","pdf_url":"https://jwcn-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-1499-2013-47","source":{"id":"https://openalex.org/S82675988","display_name":"EURASIP Journal on Wireless Communications and Networking","issn_l":"1687-1472","issn":["1687-1472","1687-1499"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Wireless Communications and Networking","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jwcn-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-1499-2013-47","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100365531","display_name":"Junjie Chen","orcid":"https://orcid.org/0000-0001-7032-2759"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Junjie Chen","raw_affiliation_strings":["Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, 76019-0016, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, 76019-0016, USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052175115","display_name":"Qilian Liang","orcid":"https://orcid.org/0000-0002-3630-8010"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qilian Liang","raw_affiliation_strings":["Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, 76019-0016, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, 76019-0016, USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034763948","display_name":"Baoju Zhang","orcid":"https://orcid.org/0000-0002-1435-7401"},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoju Zhang","raw_affiliation_strings":["College of Physics & Electronic Information, Tianjin Normal University, Tianjin, 300387, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Physics & Electronic Information, Tianjin Normal University, Tianjin, 300387, China","institution_ids":["https://openalex.org/I15062923"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056737004","display_name":"Xiaorong Wu","orcid":"https://orcid.org/0000-0002-1589-978X"},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaorong Wu","raw_affiliation_strings":["College of Physics & Electronic Information, Tianjin Normal University, Tianjin, 300387, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Physics & Electronic Information, Tianjin Normal University, Tianjin, 300387, China","institution_ids":["https://openalex.org/I15062923"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100365531"],"corresponding_institution_ids":["https://openalex.org/I189196454"],"apc_list":{"value":1665,"currency":"USD","value_usd":1665},"apc_paid":{"value":1665,"currency":"USD","value_usd":1665},"fwci":4.0472,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.93843895,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2013","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9994999766349792,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/coprime-integers","display_name":"Coprime integers","score":0.7634128332138062},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7284684181213379},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.5537993907928467},{"id":"https://openalex.org/keywords/coherent-sampling","display_name":"Coherent sampling","score":0.5430727005004883},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4928167164325714},{"id":"https://openalex.org/keywords/nyquist\u2013shannon-sampling-theorem","display_name":"Nyquist\u2013Shannon sampling theorem","score":0.47438696026802063},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.46995094418525696},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4508008658885956},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.4317163825035095},{"id":"https://openalex.org/keywords/slice-sampling","display_name":"Slice sampling","score":0.4300585389137268},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4137716293334961},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2508677840232849},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.22383037209510803},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.21740937232971191}],"concepts":[{"id":"https://openalex.org/C23230895","wikidata":"https://www.wikidata.org/wiki/Q104752","display_name":"Coprime integers","level":2,"score":0.7634128332138062},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7284684181213379},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.5537993907928467},{"id":"https://openalex.org/C31942786","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Coherent sampling","level":4,"score":0.5430727005004883},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4928167164325714},{"id":"https://openalex.org/C288623","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Nyquist\u2013Shannon sampling theorem","level":2,"score":0.47438696026802063},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.46995094418525696},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4508008658885956},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.4317163825035095},{"id":"https://openalex.org/C170593435","wikidata":"https://www.wikidata.org/wiki/Q4128565","display_name":"Slice sampling","level":4,"score":0.4300585389137268},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4137716293334961},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2508677840232849},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.22383037209510803},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.21740937232971191},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1186/1687-1499-2013-47","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-1499-2013-47","pdf_url":"https://jwcn-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-1499-2013-47","source":{"id":"https://openalex.org/S82675988","display_name":"EURASIP Journal on Wireless Communications and Networking","issn_l":"1687-1472","issn":["1687-1472","1687-1499"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Wireless Communications and Networking","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1186/1687-1499-2013-47","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-1499-2013-47","pdf_url":"https://jwcn-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-1499-2013-47","source":{"id":"https://openalex.org/S82675988","display_name":"EURASIP Journal on Wireless Communications and Networking","issn_l":"1687-1472","issn":["1687-1472","1687-1499"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Wireless Communications and Networking","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1611448503","display_name":null,"funder_award_id":"CNS-1116749","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2309762797","display_name":null,"funder_award_id":"CNS-1247848","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4166693729","display_name":"NeTS: Small: Smart Grid Wireless Networks: Capacity and Achievability","funder_award_id":"1116749","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4335402052","display_name":null,"funder_award_id":"CNS-0964713","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4686790775","display_name":"NeTS: Medium: Collaborative Research: Opportunistic and Compressive Sensing in Wireless Sensor Networks","funder_award_id":"0964713","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7471978466","display_name":null,"funder_award_id":"N00014-13-1-0043","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8209563009","display_name":"Collaborative Research: Spectrum Efficient Waveform Design with Application to Wireless Networks","funder_award_id":"1247848","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8735746605","display_name":null,"funder_award_id":"N00014-11-1-0071","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8935714593","display_name":null,"funder_award_id":"N00014-11-1-0865","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2169441574.pdf","grobid_xml":"https://content.openalex.org/works/W2169441574.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W365061972","https://openalex.org/W1514558801","https://openalex.org/W1963918507","https://openalex.org/W1988430139","https://openalex.org/W2098174516","https://openalex.org/W2099111195","https://openalex.org/W2119667497","https://openalex.org/W2127747979","https://openalex.org/W2145417574","https://openalex.org/W2149551443","https://openalex.org/W2164390589","https://openalex.org/W2478708596","https://openalex.org/W2539755345","https://openalex.org/W2987779866","https://openalex.org/W3139866291","https://openalex.org/W3163547718"],"related_works":["https://openalex.org/W2782784450","https://openalex.org/W1979849642","https://openalex.org/W3203255359","https://openalex.org/W1715660216","https://openalex.org/W4297129201","https://openalex.org/W1619692089","https://openalex.org/W2143399133","https://openalex.org/W4246955172","https://openalex.org/W3116673353","https://openalex.org/W2169441574"],"abstract_inverted_index":{"This":[0],"article":[1],"addresses":[2],"the":[3,15,57,75,86,108,116,125,132,150,171,186,192,197,204,208,212],"spectrum":[4,51,205,214],"efficiency":[5,52,55,215],"study":[6],"of":[7,17,44,59,77,98,107,110,118,127,174,196,220],"nested":[8,27,79,138,160,222],"sparse":[9,99,223],"sampling":[10,13,28,31,38,82,113,119,133,151,224],"and":[11,29,80,90,139,156,162,164,225],"coprime":[12,30,81,140,167,226],"in":[14],"estimation":[16],"power":[18,91],"spectral":[19,92],"density":[20,93],"for":[21,136,159,166],"QPSK":[22,87,188],"signal.":[23,189],"The":[24],"authors":[25],"proposed":[26],"only":[32],"showed":[33],"that":[34,124,147],"these":[35,111,178],"new":[36,218],"sub-Nyquist":[37,180],"algorithm":[39],"could":[40],"achieve":[41],"enhanced":[42,213],"degrees":[43],"freedom,":[45],"but":[46],"did":[47],"not":[48],"consider":[49],"its":[50],"performance.":[53],"Spectral":[54],"describes":[56],"ability":[58],"a":[60,67,96,217],"communication":[61],"system":[62],"to":[63,84],"accommodate":[64],"data":[65],"within":[66],"limited":[68],"bandwidth.":[69],"In":[70],"this":[71],"article,":[72],"we":[73],"give":[74],"procedures":[76],"using":[78,95],"structure":[83],"estimate":[85],"signal\u2019s":[88],"autocorrelation":[89],"(PSD)":[94],"set":[97],"samples.":[100],"We":[101],"also":[102,145],"provide":[103],"detailed":[104],"theoretical":[105],"analysis":[106],"PSD":[109,128,175],"two":[112,179],"algorithms":[114],"with":[115],"increase":[117,135],"intervals.":[120],"Our":[121,142],"results":[122,144],"prove":[123],"mainlobe":[126],"becomes":[129],"narrower":[130,184],"as":[131],"intervals":[134],"both":[137,221],"sampling.":[141,227],"simulation":[143],"show":[146],"by":[148],"making":[149],"intervals,":[152],"i.e.,":[153],"N":[154,157],"1":[155],"2":[158],"sampling,":[161,168],"P":[163],"Q":[165],"large":[169],"enough,":[170],"main":[172],"lobe":[173],"obtained":[176],"from":[177],"samplings":[181],"are":[182],"much":[183],"than":[185],"original":[187],"That":[190],"is,":[191],"bandwidth":[193],"B":[194],"occupancy":[195],"sampled":[198],"signal":[199],"is":[200,216],"smaller,":[201],"which":[202],"improves":[203],"efficiency.":[206],"Besides":[207],"smaller":[209],"average":[210],"rate,":[211],"advantage":[219]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}