{"id":"https://openalex.org/W2986739745","doi":"https://doi.org/10.1109/tvt.2019.2951594","title":"Deep Neural Network for Robust Modulation Classification Under Uncertain Noise Conditions","display_name":"Deep Neural Network for Robust Modulation Classification Under Uncertain Noise Conditions","publication_year":2019,"publication_date":"2019-11-05","ids":{"openalex":"https://openalex.org/W2986739745","doi":"https://doi.org/10.1109/tvt.2019.2951594","mag":"2986739745"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2019.2951594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2019.2951594","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5081508627","display_name":"Shisheng Hu","orcid":"https://orcid.org/0009-0004-4483-6958"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shisheng Hu","raw_affiliation_strings":["National Key Laboratory on Communications, and the Center for Intelligent Networking and Communications, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory on Communications, and the Center for Intelligent Networking and Communications, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060380113","display_name":"Yiyang Pei","orcid":"https://orcid.org/0000-0002-9915-8697"},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yiyang Pei","raw_affiliation_strings":["Singapore Institute of Technology, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-9915-8697","affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology, Singapore","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086233510","display_name":"Paul Pu Liang","orcid":"https://orcid.org/0000-0001-7768-3610"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul Pu Liang","raw_affiliation_strings":["Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA"],"raw_orcid":"https://orcid.org/0000-0001-7768-3610","affiliations":[{"raw_affiliation_string":"Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007832415","display_name":"Ying\u2010Chang Liang","orcid":"https://orcid.org/0000-0003-2671-5090"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying-Chang Liang","raw_affiliation_strings":["Center for Intelligent Networking and Communications, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-2671-5090","affiliations":[{"raw_affiliation_string":"Center for Intelligent Networking and Communications, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.448,"has_fulltext":false,"cited_by_count":151,"citation_normalized_percentile":{"value":0.98529018,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"69","issue":"1","first_page":"564","last_page":"577"},"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":0.9876999855041504,"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":0.9696000218391418,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6235754489898682},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6200088858604431},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.597902774810791},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5746544599533081},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5606412291526794},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.5501313209533691},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4766836166381836},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.44053930044174194},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39590713381767273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18959495425224304},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.11691176891326904}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6235754489898682},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6200088858604431},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.597902774810791},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5746544599533081},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5606412291526794},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.5501313209533691},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4766836166381836},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.44053930044174194},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39590713381767273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18959495425224304},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.11691176891326904},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2019.2951594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2019.2951594","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1418244083","display_name":null,"funder_award_id":"U1801261","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2599148149","display_name":"\u57fa\u4e8e\u9891\u8c31\u91cd\u6574\u6280\u672f\u7684\u8ba4\u77e5\u8702\u7a9d\u7f51\u7edc\u8bbe\u8ba1\u7406\u8bba\u4e0e\u8d44\u6e90\u4f18\u5316\u7814\u7a76","funder_award_id":"61571100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7000009495","display_name":"\u57fa\u4e8e\u5927\u6570\u636e\u7684\u590d\u6742\u5f02\u6784\u7f51\u7edc\u667a\u80fd\u65e0\u7ebf\u63a5\u5165\u7406\u8bba\u4e0e\u6280\u672f\u7814\u7a76","funder_award_id":"61631005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2054707875","https://openalex.org/W2064675550","https://openalex.org/W2107561590","https://openalex.org/W2114267371","https://openalex.org/W2130458564","https://openalex.org/W2143545157","https://openalex.org/W2143869546","https://openalex.org/W2146514432","https://openalex.org/W2146819811","https://openalex.org/W2165670531","https://openalex.org/W2170984917","https://openalex.org/W2171998198","https://openalex.org/W2272847350","https://openalex.org/W2330124749","https://openalex.org/W2481916066","https://openalex.org/W2539867171","https://openalex.org/W2545177271","https://openalex.org/W2560036562","https://openalex.org/W2562146178","https://openalex.org/W2566425973","https://openalex.org/W2617931713","https://openalex.org/W2683165743","https://openalex.org/W2741230443","https://openalex.org/W2767151733","https://openalex.org/W2767249564","https://openalex.org/W2774466702","https://openalex.org/W2795250928","https://openalex.org/W2808359495","https://openalex.org/W2810871807","https://openalex.org/W2884089434","https://openalex.org/W2891768968","https://openalex.org/W2892154397","https://openalex.org/W2893939120","https://openalex.org/W2909191390","https://openalex.org/W2916238263","https://openalex.org/W2917677817","https://openalex.org/W2939974099","https://openalex.org/W2963032608","https://openalex.org/W2963586186","https://openalex.org/W2963685106","https://openalex.org/W2963730508","https://openalex.org/W2963907541","https://openalex.org/W2963983719","https://openalex.org/W3104028856","https://openalex.org/W3105650387","https://openalex.org/W4294555862","https://openalex.org/W6631190155","https://openalex.org/W6720905350","https://openalex.org/W6728910023","https://openalex.org/W6752724743","https://openalex.org/W6917408469"],"related_works":["https://openalex.org/W4388311650","https://openalex.org/W5922282","https://openalex.org/W1974056099","https://openalex.org/W4245343541","https://openalex.org/W2386077341","https://openalex.org/W563589758","https://openalex.org/W62490179","https://openalex.org/W2954004777","https://openalex.org/W2951102138","https://openalex.org/W1568403290"],"abstract_inverted_index":{"Recently,":[0],"classifying":[1],"the":[2,58,66,92,102,109,114,122,140,163,172,180,188,197,201],"modulation":[3,28,94],"schemes":[4],"of":[5,23,57,71,116,121,191,204],"signals":[6],"using":[7,39],"deep":[8,24],"neural":[9,25,88],"network":[10,26,89],"has":[11],"received":[12],"much":[13,135],"attention.":[14],"In":[15,161],"this":[16],"paper,":[17],"we":[18],"introduce":[19],"a":[20,41,74,134],"general":[21],"model":[22],"(DNN)-based":[27],"classifiers":[29,153],"for":[30],"single-input":[31],"single-output":[32],"(SISO)":[33],"systems.":[34],"Its":[35],"feasibility":[36],"is":[37,53,80,96,106,166,184,208],"analyzed":[38,209],"maximum":[40,60],"posteriori":[42],"probability":[43],"(MAP)":[44],"criterion":[45],"and":[46,68,82,113,129,148,158,210],"its":[47,219],"robustness":[48],"to":[49,55,108,119,168,171,186,212],"uncertain":[50,110],"noise":[51,111,130,159],"conditions":[52],"compared":[54,211],"that":[56,101,120],"conventional":[59],"likelihood":[61],"(ML)-based":[62],"classifiers.":[63],"To":[64],"reduce":[65],"design":[67],"training":[69,189,198],"cost":[70],"DNN":[72,93],"classifiers,":[73,143],"simple":[75],"but":[76],"effective":[77],"pre-processing":[78,182],"method":[79,183],"introduced":[81],"adopted.":[83],"Furthermore,":[84,179],"featuring":[85],"multiple":[86],"recurrent":[87],"(RNN)":[90],"layers,":[91],"classifier":[95,105,125,165,207],"realized.":[97],"Simulation":[98],"results":[99],"show":[100],"proposed":[103,164,193,206],"RNN-based":[104],"robust":[107],"conditions,":[112],"performance":[115],"it":[117,138],"approaches":[118],"ideal":[123],"ML":[124],"with":[126,133],"perfect":[127],"channel":[128,157],"information.":[131],"Moreover,":[132],"lower":[136],"complexity,":[137],"outperforms":[139],"existing":[141],"ML-based":[142],"specifically,":[144],"expectation":[145,149],"maximization":[146,151],"(EM)":[147],"conditional":[150],"(ECM)":[152],"which":[154,216],"iteratively":[155],"estimate":[156],"parameters.":[160],"addition,":[162],"shown":[167,185],"be":[169],"invariant":[170],"signal":[173],"distortion":[174],"such":[175],"as":[176],"frequency":[177],"offset.":[178],"adopted":[181],"accelerate":[187],"process":[190],"our":[192,205],"classifier,":[194],"thus":[195],"reducing":[196],"cost.":[199],"Lastly,":[200],"computational":[202],"complexity":[203],"other":[213],"traditional":[214],"ones,":[215],"further":[217],"demonstrates":[218],"overall":[220],"advantage.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":26},{"year":2020,"cited_by_count":27}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
