{"id":"https://openalex.org/W3116964930","doi":"https://doi.org/10.1109/wcsp49889.2020.9299767","title":"Deep Learning-Based Channel Quality Estimation in Adaptive Shortwave Communication Systems","display_name":"Deep Learning-Based Channel Quality Estimation in Adaptive Shortwave Communication Systems","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3116964930","doi":"https://doi.org/10.1109/wcsp49889.2020.9299767","mag":"3116964930"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp49889.2020.9299767","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp49889.2020.9299767","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Wireless Communications and Signal Processing (WCSP)","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/A5103106238","display_name":"Yaru Zhou","orcid":"https://orcid.org/0000-0001-8143-4393"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaru Zhou","raw_affiliation_strings":["College of Telecommunications and Information Engineering, NJUPT, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, NJUPT, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017851308","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0001-7763-4261"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Wang","raw_affiliation_strings":["College of Telecommunications and Information Engineering, NJUPT, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, NJUPT, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027367677","display_name":"Guan Gui","orcid":"https://orcid.org/0000-0003-3888-2881"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guan Gui","raw_affiliation_strings":["College of Telecommunications and Information Engineering, NJUPT, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, NJUPT, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026448728","display_name":"Haris Gacanin","orcid":"https://orcid.org/0000-0003-3168-8883"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Haris Gacanin","raw_affiliation_strings":["Faculty of Electrical Engineering and Information Technology, RWTH Aachen University, Aachen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Information Technology, RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087599025","display_name":"Hikmet Sari","orcid":"https://orcid.org/0000-0001-8114-6164"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hikmet Sari","raw_affiliation_strings":["College of Telecommunications and Information Engineering, NJUPT, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, NJUPT, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1354,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58859784,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"363","last_page":"368"},"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/T11665","display_name":"Animal Vocal Communication and Behavior","score":0.9706000089645386,"subfield":{"id":"https://openalex.org/subfields/1309","display_name":"Developmental Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9624999761581421,"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/baseband","display_name":"Baseband","score":0.8610198497772217},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8211885690689087},{"id":"https://openalex.org/keywords/shortwave","display_name":"Shortwave","score":0.6510000228881836},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5798370242118835},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.578122079372406},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5218347907066345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5193473100662231},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5080666542053223},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43807467818260193},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43365657329559326},{"id":"https://openalex.org/keywords/communications-system","display_name":"Communications system","score":0.42347899079322815},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3421105742454529},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1690618395805359},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.11443006992340088},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07499960064888}],"concepts":[{"id":"https://openalex.org/C65165936","wikidata":"https://www.wikidata.org/wiki/Q575784","display_name":"Baseband","level":3,"score":0.8610198497772217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8211885690689087},{"id":"https://openalex.org/C2776272892","wikidata":"https://www.wikidata.org/wiki/Q7502249","display_name":"Shortwave","level":3,"score":0.6510000228881836},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5798370242118835},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.578122079372406},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5218347907066345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5193473100662231},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5080666542053223},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43807467818260193},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43365657329559326},{"id":"https://openalex.org/C101765175","wikidata":"https://www.wikidata.org/wiki/Q577764","display_name":"Communications system","level":2,"score":0.42347899079322815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3421105742454529},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1690618395805359},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.11443006992340088},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07499960064888},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C74902906","wikidata":"https://www.wikidata.org/wiki/Q1190858","display_name":"Radiative transfer","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/wcsp49889.2020.9299767","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp49889.2020.9299767","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:publications.rwth-aachen.de:821925","is_oa":false,"landing_page_url":"https://publications.rwth-aachen.de/record/821925","pdf_url":null,"source":{"id":"https://openalex.org/S4306401033","display_name":"RWTH Publications (RWTH Aachen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887968799","host_organization_name":"RWTH Aachen University","host_organization_lineage":["https://openalex.org/I887968799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 12th International Conference on Wireless Communications and Signal Processing : (WCSP 2020) : October 21-23, 2020, Nanjing, China / IEEE<br/>12. International Conference on Wireless Communications and Signal Processing, WCSP 2020, Nanjing, Peoples R China, 2020-10-21 - 2020-10-23","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323268","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W13066853","https://openalex.org/W1561268850","https://openalex.org/W2044131616","https://openalex.org/W2108416694","https://openalex.org/W2127495436","https://openalex.org/W2157597756","https://openalex.org/W2325434800","https://openalex.org/W2541374558","https://openalex.org/W2734408173","https://openalex.org/W2889865670","https://openalex.org/W2892154397","https://openalex.org/W2896666719","https://openalex.org/W2897036932","https://openalex.org/W2902897529","https://openalex.org/W2941806810","https://openalex.org/W2960246799","https://openalex.org/W2963145597","https://openalex.org/W2963190722","https://openalex.org/W2963290405","https://openalex.org/W2963836746","https://openalex.org/W2976103643","https://openalex.org/W2987656958","https://openalex.org/W2995894200","https://openalex.org/W2998872171","https://openalex.org/W3003174479","https://openalex.org/W3006743185","https://openalex.org/W3016146955","https://openalex.org/W3017367767","https://openalex.org/W3049287738","https://openalex.org/W6959324646"],"related_works":["https://openalex.org/W2204547643","https://openalex.org/W1497578837","https://openalex.org/W4293208944","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2355676844"],"abstract_inverted_index":{"For":[0],"a":[1,50,140],"long":[2],"time,":[3],"poor":[4],"channel":[5,27],"quality":[6,28],"and":[7,105,130,137,143,155,158],"shortage":[8],"of":[9,81,108],"frequency":[10],"resources":[11],"often":[12],"restrict":[13],"its":[14],"development.":[15],"An":[16],"adaptive":[17,36],"shortwave":[18,35],"communication":[19,37],"is":[20,31,98,123,135,139],"considered":[21],"as":[22],"an":[23],"effective":[24],"method":[25,164],"while":[26],"estimation":[29],"(CQE)":[30],"essential":[32],"for":[33,118],"the":[34,68,78,150],"system.":[38],"Currently,":[39],"deep":[40,72],"learning":[41],"(DL)":[42],"based":[43],"CQE":[44,138,163],"methods":[45,56,152],"are":[46,57,75,115,153],"proposed":[47,151],"to":[48,59,67,86,170],"achieve":[49],"good":[51],"identification":[52],"performance.":[53],"However,":[54],"existing":[55],"hard":[58],"extract":[60],"full":[61],"features":[62],"from":[63,77],"baseband":[64,100],"signals,":[65],"due":[66],"fact":[69],"that":[70,149],"their":[71],"neural":[73,132],"networks":[74],"trained":[76],"limited":[79],"length":[80],"signal":[82],"samples.":[83],"In":[84],"order":[85],"avoid":[87],"this":[88],"problem,":[89],"we":[90],"consider":[91],"two":[92],"training":[93],"models.":[94],"The":[95,120],"first":[96],"one":[97,122],"transforming":[99],"signals":[101,126,129],"into":[102,127],"constellation":[103],"diagrams":[104],"three":[106],"kinds":[107],"DL":[109],"algorithms":[110],"(i.e.,":[111],"AlexNet,":[112],"ResNet,":[113],"DenseNet)":[114],"applied":[116,136],"respectively":[117],"training.":[119],"second":[121],"slicing":[124],"IQ":[125],"multi-slices":[128],"convolutional":[131],"network":[133],"(CNN)":[134],"joint":[141,156],"multi-slice":[142,157],"cooperative":[144,159],"decision.":[145],"Experimental":[146],"results":[147],"show":[148],"robust,":[154],"detection":[160],"aided":[161],"DL-based":[162],"achieves":[165],"better":[166],"performance":[167],"even":[168],"up":[169],"100%.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
