{"id":"https://openalex.org/W2771112469","doi":"https://doi.org/10.1109/tsp.2017.2781648","title":"A Compressed Sensing Approach to Block-Iterative Equalizers","display_name":"A Compressed Sensing Approach to Block-Iterative Equalizers","publication_year":2017,"publication_date":"2017-12-08","ids":{"openalex":"https://openalex.org/W2771112469","doi":"https://doi.org/10.1109/tsp.2017.2781648","mag":"2771112469"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2017.2781648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2781648","pdf_url":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050579578","display_name":"Rafael Gustavo da Cunha Pereira Pinto","orcid":null},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rafael G. da Cunha Pereira Pinto","raw_affiliation_strings":["Federal University of Rio de Janeiro, Rio de Janeiro, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Rio de Janeiro, Rio de Janeiro, Brazil","institution_ids":["https://openalex.org/I122140584"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078577025","display_name":"Ricardo Merched","orcid":"https://orcid.org/0000-0001-5280-2767"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ricardo Merched","raw_affiliation_strings":["Department\u00a0of Electronics and Computer Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-5280-2767","affiliations":[{"raw_affiliation_string":"Department\u00a0of Electronics and Computer Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil","institution_ids":["https://openalex.org/I122140584"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I122140584"],"apc_list":null,"apc_paid":null,"fwci":0.988,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75211913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"66","issue":"4","first_page":"1007","last_page":"1022"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9995999932289124,"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":0.9988999962806702,"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/underdetermined-system","display_name":"Underdetermined system","score":0.8719859719276428},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6738293766975403},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.663213849067688},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6432196497917175},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6058486700057983},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.5462285280227661},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5011475086212158},{"id":"https://openalex.org/keywords/matched-filter","display_name":"Matched filter","score":0.43955281376838684},{"id":"https://openalex.org/keywords/constellation-diagram","display_name":"Constellation diagram","score":0.4300059378147125},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.351895272731781},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.32167285680770874},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.26170021295547485},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2102687954902649}],"concepts":[{"id":"https://openalex.org/C179690561","wikidata":"https://www.wikidata.org/wiki/Q4316110","display_name":"Underdetermined system","level":2,"score":0.8719859719276428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6738293766975403},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.663213849067688},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6432196497917175},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6058486700057983},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.5462285280227661},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5011475086212158},{"id":"https://openalex.org/C50151734","wikidata":"https://www.wikidata.org/wiki/Q1759577","display_name":"Matched filter","level":3,"score":0.43955281376838684},{"id":"https://openalex.org/C185837786","wikidata":"https://www.wikidata.org/wiki/Q1782940","display_name":"Constellation diagram","level":4,"score":0.4300059378147125},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.351895272731781},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.32167285680770874},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.26170021295547485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2102687954902649},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2017.2781648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2781648","pdf_url":null,"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":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W340244495","https://openalex.org/W368469426","https://openalex.org/W1490457205","https://openalex.org/W1527438800","https://openalex.org/W1542278698","https://openalex.org/W1606219475","https://openalex.org/W1667165204","https://openalex.org/W1980454827","https://openalex.org/W1980466464","https://openalex.org/W2007934573","https://openalex.org/W2015418199","https://openalex.org/W2046245205","https://openalex.org/W2046658845","https://openalex.org/W2081541477","https://openalex.org/W2099641086","https://openalex.org/W2100328514","https://openalex.org/W2105502728","https://openalex.org/W2109246257","https://openalex.org/W2110988249","https://openalex.org/W2129131372","https://openalex.org/W2133475491","https://openalex.org/W2137779356","https://openalex.org/W2145096794","https://openalex.org/W2151999766","https://openalex.org/W2154332973","https://openalex.org/W2172201990","https://openalex.org/W3016197797","https://openalex.org/W4239240501","https://openalex.org/W4240458502","https://openalex.org/W4250589301","https://openalex.org/W4300263211","https://openalex.org/W6629426345","https://openalex.org/W6631525491","https://openalex.org/W6636283306","https://openalex.org/W6675897046"],"related_works":["https://openalex.org/W2549922247","https://openalex.org/W2300663769","https://openalex.org/W1523391825","https://openalex.org/W2152231009","https://openalex.org/W1939631077","https://openalex.org/W2735239078","https://openalex.org/W2152589265","https://openalex.org/W2071589878","https://openalex.org/W2963414100","https://openalex.org/W2372875289"],"abstract_inverted_index":{"The":[0,172],"universality":[1],"of":[2,9,31,49,69,76,84,91,104,120,129,141,164,217],"underdetermined":[3],"systems":[4],"has":[5],"nurtured":[6],"a":[7,37,117,147,178],"variety":[8],"novel":[10],"compressed":[11],"sensing":[12],"(CS)":[13],"algorithms":[14,194],"that":[15,143,204],"ingeniously":[16],"exploit":[17],"data":[18],"sparsity.":[19],"Whereas":[20],"well-studied":[21],"greedy":[22],"and":[23,161,169],"iterative":[24,51,174],"threshold-based":[25],"CS":[26,85,148],"recursions":[27],"take":[28],"the":[29,47,59,66,74,88,123,130,152,192,215,218],"form":[30,140],"an":[32],"adaptive":[33],"filter":[34],"followed":[35],"by":[36,58],"proximal":[38],"operator,":[39],"this":[40],"is":[41,55,94,114,132,162],"no":[42,158],"different":[43],"in":[44,82,109,211],"spirit":[45],"from":[46],"role":[48],"block":[50,110,135],"equalizers,":[52],"where":[53,87,112],"structure":[54],"roughly":[56],"exploited":[57],"signal":[60,70],"constellation":[61],"slicer.":[62],"By":[63],"capitalizing":[64],"on":[65,207],"intrinsic":[67],"sparsity":[68],"modulations,":[71],"we":[72],"approach":[73],"concept":[75],"interblock":[77],"interference":[78],"(IBI)":[79],"more":[80,179],"proficiently":[81],"light":[83],"concepts,":[86],"optimal":[89],"feedback":[90],"detected":[92],"symbols":[93],"devised":[95],"adaptively.":[96],"This":[97],"should":[98],"be":[99],"contrasted":[100],"with":[101],"standard":[102],"forms":[103],"IBI":[105,170],"estimation/cancellation":[106],"commonly":[107,137],"seen":[108],"DFEs,":[111],"detection":[113],"restricted":[115],"to":[116,151,201],"contiguous":[118],"set":[119],"entries":[121],"within":[122],"transmitted":[124,154],"vector.":[125],"A":[126],"significant":[127],"consequence":[128],"latter":[131],"that,":[133],"while":[134],"transceivers":[136],"employ":[138],"some":[139],"redundancy":[142,159],"accounts":[144],"for":[145],"IBI,":[146],"algorithm":[149],"applied":[150],"same":[153],"vector":[155],"may":[156],"require":[157],"whatsoever,":[160],"capable":[163],"retrieving":[165],"both":[166],"target":[167],"symbol":[168],"altogether.":[171],"CS-based":[173],"DFE":[175],"acts":[176],"as":[177],"efficient":[180],"re-estimation":[181],"procedure,":[182],"proposed":[183],"under":[184],"recursive-least-squares":[185],"based":[186],"adaptations.":[187],"Besides":[188],"maximizing":[189],"system":[190],"throughput,":[191],"new":[193],"exhibit":[195],"significantly":[196],"higher":[197],"performance":[198],"when":[199],"compared":[200],"existing":[202],"methods":[203],"focus":[205],"solely":[206],"minimized":[208],"redundancy.":[209],"Simulations":[210],"several":[212],"scenarios":[213],"illustrate":[214],"merits":[216],"unified":[219],"approaches.":[220]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
