{"id":"https://openalex.org/W2474743654","doi":"https://doi.org/10.1109/vtcspring.2016.7504109","title":"A Sparsity-Based Clustering Framework for Radio Channel Impulse Responses","display_name":"A Sparsity-Based Clustering Framework for Radio Channel Impulse Responses","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2474743654","doi":"https://doi.org/10.1109/vtcspring.2016.7504109","mag":"2474743654"},"language":"en","primary_location":{"id":"doi:10.1109/vtcspring.2016.7504109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcspring.2016.7504109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5012250827","display_name":"Ruisi He","orcid":"https://orcid.org/0000-0003-4135-3227"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruisi He","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100344294","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0001-5090-9915"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620739","display_name":"Bo Ai","orcid":"https://orcid.org/0000-0001-6850-0595"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Ai","raw_affiliation_strings":["State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071725365","display_name":"Andreas F. Molisch","orcid":"https://orcid.org/0000-0002-4779-4763"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas F. Molisch","raw_affiliation_strings":["Department of Electrical Engineering, University of Southern California, Los Angeles, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391896","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-1717-5785"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Institute of Communications and Navigation, German Aerospace Center, Wessling, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Communications and Navigation, German Aerospace Center, Wessling, Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350955","display_name":"Zhangdui Zhong","orcid":"https://orcid.org/0000-0001-8889-7374"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangdui Zhong","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027501725","display_name":"Jian Yu","orcid":"https://orcid.org/0000-0002-9488-5182"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yu","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062897844","display_name":"Seun Sangodoyin","orcid":"https://orcid.org/0000-0002-1215-9778"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seun Sangodoyin","raw_affiliation_strings":["Department of Electrical Engineering, University of Southern California, Los Angeles, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12024","display_name":"Ultra-Wideband Communications Technology","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T12024","display_name":"Ultra-Wideband Communications Technology","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11158","display_name":"Wireless Networks and Protocols","score":0.9972000122070312,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.8894366025924683},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6843515634536743},{"id":"https://openalex.org/keywords/impulse","display_name":"Impulse (physics)","score":0.595443606376648},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5888925790786743},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.574711799621582},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5530303120613098},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.48191311955451965},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4664544463157654},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4483656585216522},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44624465703964233},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.331470251083374},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31512296199798584},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.070240318775177}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8894366025924683},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6843515634536743},{"id":"https://openalex.org/C70836080","wikidata":"https://www.wikidata.org/wiki/Q837940","display_name":"Impulse (physics)","level":2,"score":0.595443606376648},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5888925790786743},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.574711799621582},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5530303120613098},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.48191311955451965},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4664544463157654},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4483656585216522},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44624465703964233},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.331470251083374},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31512296199798584},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.070240318775177},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtcspring.2016.7504109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcspring.2016.7504109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W874067465","https://openalex.org/W1889613222","https://openalex.org/W2004658770","https://openalex.org/W2016939110","https://openalex.org/W2026534096","https://openalex.org/W2102509933","https://openalex.org/W2103903472","https://openalex.org/W2107861471","https://openalex.org/W2110618891","https://openalex.org/W2121004630","https://openalex.org/W2124664912","https://openalex.org/W2125324284","https://openalex.org/W2127305130","https://openalex.org/W2129727074","https://openalex.org/W2134829276","https://openalex.org/W2137790917","https://openalex.org/W2138483811","https://openalex.org/W2138722122","https://openalex.org/W2140089063","https://openalex.org/W2141474913","https://openalex.org/W2143738441","https://openalex.org/W2153233077","https://openalex.org/W2161042721","https://openalex.org/W2163363194","https://openalex.org/W2168246258","https://openalex.org/W2333715204","https://openalex.org/W2962781485","https://openalex.org/W3107179866","https://openalex.org/W6639387936","https://openalex.org/W6655042798"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"In":[0],"this":[1,120],"paper,":[2],"we":[3],"propose":[4],"a":[5,14,38,58],"novel":[6],"channel":[7],"impulse":[8],"response":[9],"(CIR)":[10],"clustering":[11,74,97],"algorithm":[12,88],"using":[13,50],"sparsity-based":[15,39],"method,":[16],"which":[17,44,70],"exploits":[18],"the":[19,67,83,90,96,107,127],"feature":[20],"of":[21,25,93,106,115,130],"CIR":[22,128],"that":[23],"power":[24],"multipath":[26],"component":[27],"(MPC)":[28],"is":[29,61],"exponentially":[30],"decreasing":[31],"with":[32,102],"increasing":[33],"delay.":[34],"We":[35],"first":[36],"use":[37],"optimization":[40],"to":[41,63,72,78,125],"recover":[42],"CIRs,":[43,69],"can":[45,122],"be":[46,123],"well":[47],"solved":[48],"by":[49],"reweighted":[51],"\u2113":[52],"<sub":[53],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[54],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[55],"minimization.":[56],"Then":[57],"heuristic":[59],"approach":[60],"provided":[62],"identify":[64],"clusters":[65,80],"in":[66,76,82,119],"recovered":[68],"leads":[71],"improved":[73],"accuracy":[75],"comparison":[77],"identifying":[79],"directly":[81],"raw":[84],"CIRs.":[85],"The":[86,117],"proposed":[87],"incorporates":[89],"physical":[91],"behaviors":[92],"MPCs":[94],"into":[95],"framework":[98],"and":[99,112],"enables":[100],"applications":[101],"no":[103],"prior":[104],"knowledge":[105],"clusters,":[108],"such":[109],"as":[110],"number":[111],"initial":[113],"locations":[114],"clusters.":[116],"results":[118],"paper":[121],"used":[124],"parameterize":[126],"model":[129],"radio":[131],"channels.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}