{"id":"https://openalex.org/W3165893772","doi":"https://doi.org/10.1109/ieeeconf51394.2020.9443424","title":"Over The Air Performance of Deep Learning for Modulation Classification across Channel Conditions","display_name":"Over The Air Performance of Deep Learning for Modulation Classification across Channel Conditions","publication_year":2020,"publication_date":"2020-11-01","ids":{"openalex":"https://openalex.org/W3165893772","doi":"https://doi.org/10.1109/ieeeconf51394.2020.9443424","mag":"3165893772"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf51394.2020.9443424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf51394.2020.9443424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","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/A5068305108","display_name":"Venkatesh Sathyanarayanan","orcid":"https://orcid.org/0000-0002-0834-0697"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Venkatesh Sathyanarayanan","raw_affiliation_strings":["University of California, San Diego, La Jolla, USA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, La Jolla, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020298722","display_name":"Mark Wagner","orcid":"https://orcid.org/0000-0002-2153-7080"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Wagner","raw_affiliation_strings":["University of California, San Diego, La Jolla, USA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, La Jolla, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004718675","display_name":"Peter Gerstoft","orcid":"https://orcid.org/0000-0002-0471-062X"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter Gerstoft","raw_affiliation_strings":["University of California, San Diego, La Jolla, USA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, La Jolla, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5068305108"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":0.5302,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74363594,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"157","last_page":"161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":1.0,"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":1.0,"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":0.9872999787330627,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7537635564804077},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7513623237609863},{"id":"https://openalex.org/keywords/non-line-of-sight-propagation","display_name":"Non-line-of-sight propagation","score":0.6073659658432007},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6032952070236206},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5892024040222168},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.5792267918586731},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5234836339950562},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4904038906097412},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.47012054920196533},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4691397547721863},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.46692487597465515},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44130876660346985},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.42597246170043945},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38459813594818115},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.20838838815689087},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12857568264007568},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08643582463264465}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7537635564804077},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7513623237609863},{"id":"https://openalex.org/C154910267","wikidata":"https://www.wikidata.org/wiki/Q1740982","display_name":"Non-line-of-sight propagation","level":3,"score":0.6073659658432007},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6032952070236206},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5892024040222168},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5792267918586731},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5234836339950562},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4904038906097412},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.47012054920196533},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4691397547721863},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.46692487597465515},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44130876660346985},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.42597246170043945},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38459813594818115},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.20838838815689087},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12857568264007568},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08643582463264465},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf51394.2020.9443424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf51394.2020.9443424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1552439670","https://openalex.org/W1686810756","https://openalex.org/W1839281361","https://openalex.org/W2035328597","https://openalex.org/W2035922088","https://openalex.org/W2272847350","https://openalex.org/W2330798483","https://openalex.org/W2400933646","https://openalex.org/W2540696201","https://openalex.org/W2560036562","https://openalex.org/W2603396821","https://openalex.org/W2612824601","https://openalex.org/W2734408173","https://openalex.org/W2773170971","https://openalex.org/W2883112362","https://openalex.org/W2886161635","https://openalex.org/W2888848736","https://openalex.org/W2889017409","https://openalex.org/W2963115134","https://openalex.org/W2963809753","https://openalex.org/W6637373629","https://openalex.org/W6694508510"],"related_works":["https://openalex.org/W2123376283","https://openalex.org/W4387327236","https://openalex.org/W2183488467","https://openalex.org/W2028462208","https://openalex.org/W1990237101","https://openalex.org/W4309907966","https://openalex.org/W4387896287","https://openalex.org/W4285337533","https://openalex.org/W2982831492","https://openalex.org/W2187490799"],"abstract_inverted_index":{"Deep":[0],"learning":[1,71,170],"(DL)":[2],"models":[3,72,131,147],"used":[4,166],"for":[5,75,153,161,167],"modulation":[6,42,139],"classification":[7],"are":[8,79,125,132,151],"mostly":[9],"trained":[10,89],"on":[11,18,45,81,90,148],"simulated":[12,29],"data.":[13,32,47,65],"Their":[14],"performance":[15,53],"drops":[16],"significantly":[17],"real":[19,31,46,149],"test":[20,64,100],"data,":[21,150],"due":[22,55],"to":[23,56,84],"disparity":[24,57],"in":[25,58],"probability":[26,59],"distributions":[27,60],"between":[28,61],"and":[30,63,91,99,112,119,141,163],"The":[33],"eventual":[34],"goal":[35],"is":[36,159],"building":[37],"a":[38],"DL":[39,146],"model":[40,135],"classifying":[41],"type":[43],"accurately":[44],"This":[48],"work":[49],"empirically":[50],"studies":[51],"the":[52,130],"impact":[54],"training":[62,98],"We":[66],"borrow":[67],"best":[68],"performing":[69],"deep":[70,169],"from":[73],"literature":[74],"our":[76],"analysis.":[77],"Models":[78],"tested":[80],"data":[82,101],"belonging":[83],"channel":[85,103,137],"conditions":[86,104],"they":[87],"were":[88],"otherwise.":[92],"Software":[93],"defined":[94],"radios":[95],"(SDR)":[96],"collect":[97],"under":[102],"of":[105,129,145,156],"additive":[106],"white":[107],"Gaussian":[108],"noise,":[109],"line-of-sight":[110],"(LOS)":[111],"non-line-of-sight":[113],"(NLOS).":[114],"Convolutional":[115],"neural":[116,121],"network":[117,122],"(CNN)":[118],"Residual":[120],"(ResNet)":[123],"architectures":[124],"used.":[126],"Test":[127],"accuracies":[128],"compared":[133],"across":[134],"architectures,":[136],"conditions,":[138],"types":[140],"SNR.":[142],"Performance":[143],"results":[144],"presented":[152],"wide":[154],"set":[155],"scenarios.":[157],"Dataset":[158],"available":[160],"download":[162],"can":[164],"be":[165],"evaluating":[168],"models.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}