{"id":"https://openalex.org/W2996613410","doi":"https://doi.org/10.1109/dyspan.2019.8935684","title":"Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments","display_name":"Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W2996613410","doi":"https://doi.org/10.1109/dyspan.2019.8935684","mag":"2996613410"},"language":"en","primary_location":{"id":"doi:10.1109/dyspan.2019.8935684","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dyspan.2019.8935684","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","raw_type":"proceedings-article"},"type":"preprint","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/A5054863127","display_name":"Yi Shi","orcid":"https://orcid.org/0000-0002-6110-3084"},"institutions":[{"id":"https://openalex.org/I4210130203","display_name":"Intelligent Automation (United States)","ror":"https://ror.org/02fwb6r86","country_code":"US","type":"company","lineage":["https://openalex.org/I4210130203"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yi Shi","raw_affiliation_strings":["Intelligent Automation, Inc., Rockville, MD, USA"],"affiliations":[{"raw_affiliation_string":"Intelligent Automation, Inc., Rockville, MD, USA","institution_ids":["https://openalex.org/I4210130203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075960743","display_name":"Kemal Davasl\u0131o\u011flu","orcid":"https://orcid.org/0000-0003-2745-6764"},"institutions":[{"id":"https://openalex.org/I4210130203","display_name":"Intelligent Automation (United States)","ror":"https://ror.org/02fwb6r86","country_code":"US","type":"company","lineage":["https://openalex.org/I4210130203"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kemal Davaslioglu","raw_affiliation_strings":["Intelligent Automation, Inc., Rockville, MD, USA"],"affiliations":[{"raw_affiliation_string":"Intelligent Automation, Inc., Rockville, MD, USA","institution_ids":["https://openalex.org/I4210130203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089570143","display_name":"Yalin E. Sagduyu","orcid":"https://orcid.org/0000-0003-1576-5527"},"institutions":[{"id":"https://openalex.org/I4210130203","display_name":"Intelligent Automation (United States)","ror":"https://ror.org/02fwb6r86","country_code":"US","type":"company","lineage":["https://openalex.org/I4210130203"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yalin E. Sagduyu","raw_affiliation_strings":["Intelligent Automation, Inc., Rockville, MD, USA"],"affiliations":[{"raw_affiliation_string":"Intelligent Automation, Inc., Rockville, MD, USA","institution_ids":["https://openalex.org/I4210130203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110245984","display_name":"William C. Headley","orcid":"https://orcid.org/0000-0001-6306-072X"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William C. Headley","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075822978","display_name":"Michael C. Fowler","orcid":"https://orcid.org/0000-0002-7538-231X"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Fowler","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084789750","display_name":"Gilbert Green","orcid":null},"institutions":[{"id":"https://openalex.org/I1304082316","display_name":"United States Department of the Army","ror":"https://ror.org/035w1gb98","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gilbert Green","raw_affiliation_strings":["US Army, APG, MD, USA"],"affiliations":[{"raw_affiliation_string":"US Army, APG, MD, USA","institution_ids":["https://openalex.org/I1304082316"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5054863127"],"corresponding_institution_ids":["https://openalex.org/I4210130203"],"apc_list":null,"apc_paid":null,"fwci":9.1059,"has_fulltext":false,"cited_by_count":110,"citation_normalized_percentile":{"value":0.98242183,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11447","display_name":"Blind Source Separation Techniques","score":0.9771000146865845,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7963131666183472},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.493811696767807},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4514341950416565},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4173596203327179},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4147942066192627},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.4147590398788452},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.40998393297195435},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40516990423202515},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3537222743034363},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3451751470565796},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.3281477093696594},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1615450084209442}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7963131666183472},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.493811696767807},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4514341950416565},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4173596203327179},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4147942066192627},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.4147590398788452},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.40998393297195435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40516990423202515},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3537222743034363},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3451751470565796},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.3281477093696594},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1615450084209442}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dyspan.2019.8935684","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dyspan.2019.8935684","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1666202160","https://openalex.org/W1980262437","https://openalex.org/W2005956500","https://openalex.org/W2113839990","https://openalex.org/W2125835628","https://openalex.org/W2128569883","https://openalex.org/W2133069808","https://openalex.org/W2159073043","https://openalex.org/W2272847350","https://openalex.org/W2402144811","https://openalex.org/W2535388113","https://openalex.org/W2560036562","https://openalex.org/W2560647685","https://openalex.org/W2580817561","https://openalex.org/W2616108305","https://openalex.org/W2617896574","https://openalex.org/W2754643364","https://openalex.org/W2764155154","https://openalex.org/W2773170971","https://openalex.org/W2853090665","https://openalex.org/W2907201671","https://openalex.org/W2908997014","https://openalex.org/W2953384591","https://openalex.org/W2963047971","https://openalex.org/W2963079272","https://openalex.org/W2963115134","https://openalex.org/W2963190722","https://openalex.org/W2964067969","https://openalex.org/W2964121744","https://openalex.org/W2964277700","https://openalex.org/W2971480956","https://openalex.org/W3100857292","https://openalex.org/W4243563432","https://openalex.org/W4297817495","https://openalex.org/W6631190155","https://openalex.org/W6677258307","https://openalex.org/W6679756777","https://openalex.org/W6713134421","https://openalex.org/W6738862474","https://openalex.org/W6745580566","https://openalex.org/W6757355660"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4380075502","https://openalex.org/W4291897433","https://openalex.org/W4223943233"],"abstract_inverted_index":{"Dynamic":[0],"spectrum":[1,209],"access":[2,204],"(DSA)":[3],"benefits":[4],"from":[5,91],"detection":[6,125],"and":[7,17,79,101,138,206,220,244],"classification":[8,35,186,199,235],"of":[9,130],"interference":[10,90,215],"sources":[11],"including":[12],"in-network":[13,194,241],"users,":[14,16],"out-network":[15,217,245],"jammers":[18,74],"that":[19,229],"may":[20,47,55,67,84],"all":[21],"coexist":[22],"in":[23,37,188],"a":[24,29,38,103,189],"wireless":[25,40],"network.":[26],"We":[27,182],"present":[28],"deep":[30],"learning":[31,100],"based":[32,114],"signal":[33,45,53,77,82,163,185,198,234],"(modulation)":[34],"solution":[36],"realistic":[39],"network":[41],"setting,":[42],"where":[43,193],"1)":[44],"types":[46,54,83],"change":[48],"over":[49],"time;":[50],"2)":[51],"some":[52],"be":[56,68,85],"unknown":[57,121],"for":[58],"which":[59],"there":[60],"is":[61],"no":[62],"training":[63],"data;":[64],"3)":[65],"signals":[66,122],"spoofed":[69],"such":[70],"as":[71],"the":[72,89,128,147,161,184,208],"smart":[73],"replaying":[75],"other":[76,212],"types;":[78],"4)":[80],"different":[81],"superimposed":[86],"due":[87,154],"to":[88,127,150,155,159,178,201,240],"concurrent":[92],"transmissions.":[93],"For":[94,116,142,165],"case":[95,117,143,166],"1,":[96],"we":[97,119,145,168,227],"apply":[98,169],"continual":[99],"train":[102],"Convolutional":[104],"Neural":[105],"Network":[106],"(CNN)":[107],"using":[108,133,173],"an":[109],"Elastic":[110],"Weight":[111],"Consolidation":[112],"(EWC)":[113],"loss.":[115],"2,":[118],"detect":[120],"via":[123],"outlier":[124],"applied":[126],"outputs":[129],"convolutional":[131],"layers":[132],"Minimum":[134],"Covariance":[135],"Determinant":[136],"(MCD)":[137],"k-means":[139],"clustering":[140],"methods.":[141],"3,":[144],"extend":[146],"CNN":[148],"structure":[149],"capture":[151],"phase":[152],"shifts":[153],"radio":[156],"hardware":[157],"effects":[158],"identify":[160],"spoofing":[162],"sources.":[164],"4,":[167],"blind":[170],"source":[171],"separation":[172],"Independent":[174],"Component":[175],"Analysis":[176],"(ICA)":[177],"separate":[179],"interfering":[180],"signals.":[181],"utilize":[183],"results":[187,236],"distributed":[190,230],"scheduling":[191,231],"protocol,":[192],"(secondary)":[195],"users":[196,219],"employ":[197],"scores":[200],"make":[202],"channel":[203],"decisions":[205],"share":[207],"with":[210,216,223],"each":[211],"while":[213],"avoiding":[214],"(primary)":[218],"jammers.":[221],"Compared":[222],"benchmark":[224],"TDMA-based":[225],"schemes,":[226],"show":[228],"constructed":[232],"upon":[233],"provides":[237],"major":[238],"improvements":[239],"user":[242,246],"throughput":[243],"success":[247],"ratio.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":26},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":4}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}