{"id":"https://openalex.org/W2908297746","doi":"https://doi.org/10.1109/ccwc.2019.8666489","title":"Impulsive Noise Detection in OFDM-based Systems: A Deep Learning Perspective","display_name":"Impulsive Noise Detection in OFDM-based Systems: A Deep Learning Perspective","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2908297746","doi":"https://doi.org/10.1109/ccwc.2019.8666489","mag":"2908297746"},"language":"en","primary_location":{"id":"doi:10.1109/ccwc.2019.8666489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc.2019.8666489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-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/A5072904820","display_name":"Reza Barazideh","orcid":"https://orcid.org/0000-0002-2102-0639"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Reza Barazideh","raw_affiliation_strings":["Dep. Elec. and Com. Eng., Kansas State University, Manhattan, KS, USA"],"affiliations":[{"raw_affiliation_string":"Dep. Elec. and Com. Eng., Kansas State University, Manhattan, KS, USA","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058404264","display_name":"Solmaz Niknam","orcid":"https://orcid.org/0000-0003-3538-7869"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Solmaz Niknam","raw_affiliation_strings":["Dep. Elec. and Com. Eng., Kansas State University, Manhattan, KS, USA"],"affiliations":[{"raw_affiliation_string":"Dep. Elec. and Com. Eng., Kansas State University, Manhattan, KS, USA","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003778401","display_name":"Balasubramaniam Natarajan","orcid":"https://orcid.org/0000-0001-6429-9003"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Balasubramaniam Natarajan","raw_affiliation_strings":["Dep. Elec. and Com. Eng., Kansas State University, Manhattan, KS, USA"],"affiliations":[{"raw_affiliation_string":"Dep. Elec. and Com. Eng., Kansas State University, Manhattan, KS, USA","institution_ids":["https://openalex.org/I189590672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072904820"],"corresponding_institution_ids":["https://openalex.org/I189590672"],"apc_list":null,"apc_paid":null,"fwci":1.9383,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.8613896,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"0937","last_page":"0942"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12146","display_name":"Power Line Communications and Noise","score":1.0,"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/T12146","display_name":"Power Line Communications and Noise","score":1.0,"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/T11444","display_name":"Electromagnetic Compatibility and Noise Suppression","score":0.9966999888420105,"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/T11873","display_name":"PAPR reduction in OFDM","score":0.98580002784729,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.7226371169090271},{"id":"https://openalex.org/keywords/orthogonal-frequency-division-multiplexing","display_name":"Orthogonal frequency-division multiplexing","score":0.7076971530914307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6643761396408081},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5376141667366028},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4697316884994507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39639967679977417},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.386570543050766},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.28509336709976196},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13684386014938354},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.08948752284049988}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7226371169090271},{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.7076971530914307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6643761396408081},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5376141667366028},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4697316884994507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39639967679977417},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.386570543050766},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.28509336709976196},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13684386014938354},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.08948752284049988},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccwc.2019.8666489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc.2019.8666489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)","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":26,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1540920731","https://openalex.org/W2006862994","https://openalex.org/W2027354944","https://openalex.org/W2060990338","https://openalex.org/W2094178220","https://openalex.org/W2111096422","https://openalex.org/W2125041499","https://openalex.org/W2138283263","https://openalex.org/W2157903917","https://openalex.org/W2160211582","https://openalex.org/W2160817147","https://openalex.org/W2335170426","https://openalex.org/W2786098118","https://openalex.org/W2901587720","https://openalex.org/W2921436777","https://openalex.org/W2962867218","https://openalex.org/W2963391674","https://openalex.org/W2963536990","https://openalex.org/W2963939962","https://openalex.org/W2964121744","https://openalex.org/W6631943919","https://openalex.org/W6752153194","https://openalex.org/W6755901227","https://openalex.org/W6760331446"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W2939353110","https://openalex.org/W2126887587","https://openalex.org/W4230611425","https://openalex.org/W2948658236","https://openalex.org/W2941846814","https://openalex.org/W3118091236","https://openalex.org/W3164822677"],"abstract_inverted_index":{"Efficient":[0],"removal":[1],"of":[2,48,65,77,100],"impulsive":[3,118],"noise":[4],"(IN)":[5],"from":[6],"received":[7],"signal":[8],"is":[9,42,54,123],"essential":[10],"in":[11,56],"many":[12],"communication":[13,31],"applications.":[14],"In":[15,33],"this":[16,78],"paper,":[17],"we":[18],"propose":[19],"a":[20,37],"two":[21],"stage":[22,59],"IN":[23,53,108],"mitigation":[24],"approach":[25,79,103],"for":[26,111],"orthogonal":[27],"frequency-division":[28],"multiplexing":[29],"(OFDM)-based":[30],"systems.":[32],"the":[34,46,51,57,62,70,94,98,101,121],"first":[35],"stage,":[36],"deep":[38],"neural":[39],"network":[40],"(DNN)":[41],"used":[43],"to":[44,60,81,92],"detect":[45,93],"instances":[47],"impulsivity.":[49],"Then,":[50],"detected":[52],"blanked":[55],"suppression":[58],"alleviate":[61],"harmful":[63],"effects":[64],"outliers.":[66],"Simulation":[67],"results":[68],"demonstrate":[69,97],"superior":[71],"bit":[72],"error":[73],"rate":[74],"(BER)":[75],"performance":[76],"relative":[80],"classic":[82],"approaches":[83],"such":[84],"as":[85],"blanking":[86],"and":[87,113,115],"clipping":[88],"that":[89],"use":[90],"threshold":[91],"IN.":[95],"We":[96],"robustness":[99],"DNN-based":[102],"under":[104],"(i)":[105],"mismatch":[106],"between":[107],"models":[109],"considered":[110],"training":[112],"testing,":[114],"(ii)":[116],"bursty":[117],"environment":[119],"when":[120],"receiver":[122],"empowered":[124],"with":[125],"interleaving":[126],"techniques.":[127]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}