{"id":"https://openalex.org/W2963852693","doi":"https://doi.org/10.1109/iswcs.2018.8491056","title":"Joint Neural Network Equalizer and Decoder","display_name":"Joint Neural Network Equalizer and Decoder","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2963852693","doi":"https://doi.org/10.1109/iswcs.2018.8491056","mag":"2963852693"},"language":"en","primary_location":{"id":"doi:10.1109/iswcs.2018.8491056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iswcs.2018.8491056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th International Symposium on Wireless Communication Systems (ISWCS)","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/A5039571679","display_name":"Weihong Xu","orcid":"https://orcid.org/0000-0003-3766-3353"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Weihong Xu","raw_affiliation_strings":["National Mobile Communications Research Laboratory"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035738969","display_name":"Zhiwei Zhong","orcid":"https://orcid.org/0000-0003-2213-9495"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiwei Zhong","raw_affiliation_strings":["National Mobile Communications Research Laboratory"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031039322","display_name":"Y. Be'ery","orcid":"https://orcid.org/0000-0001-9642-8391"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yair Be'ery","raw_affiliation_strings":["School of Electrical Engineering, Tel-Aviv University, Israel"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Tel-Aviv University, Israel","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072916702","display_name":"Xiaohu You","orcid":"https://orcid.org/0000-0002-0809-8511"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaohu You","raw_affiliation_strings":["National Mobile Communications Research Laboratory"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100380082","display_name":"Chuan Zhang","orcid":"https://orcid.org/0000-0002-7736-6487"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuan Zhang","raw_affiliation_strings":["National Mobile Communications Research Laboratory"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5039571679"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.9898,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.96269774,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/decodes","display_name":"Decodes","score":0.8615893125534058},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7796831130981445},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6770231127738953},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6640838980674744},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.6207852959632874},{"id":"https://openalex.org/keywords/equalization","display_name":"Equalization (audio)","score":0.5956305861473083},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5861733555793762},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5516263246536255},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5196548700332642},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5112040042877197},{"id":"https://openalex.org/keywords/soft-decision-decoder","display_name":"Soft-decision decoder","score":0.47798842191696167},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4717101752758026},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44727545976638794},{"id":"https://openalex.org/keywords/equalizer","display_name":"Equalizer","score":0.4404953718185425},{"id":"https://openalex.org/keywords/blind-equalization","display_name":"Blind equalization","score":0.4108756184577942},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3979123830795288},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39719700813293457},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.19340449571609497},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09764587879180908}],"concepts":[{"id":"https://openalex.org/C2778858076","wikidata":"https://www.wikidata.org/wiki/Q5249539","display_name":"Decodes","level":3,"score":0.8615893125534058},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7796831130981445},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6770231127738953},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6640838980674744},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.6207852959632874},{"id":"https://openalex.org/C75755367","wikidata":"https://www.wikidata.org/wiki/Q104531076","display_name":"Equalization (audio)","level":3,"score":0.5956305861473083},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5861733555793762},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5516263246536255},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5196548700332642},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5112040042877197},{"id":"https://openalex.org/C185588885","wikidata":"https://www.wikidata.org/wiki/Q7553811","display_name":"Soft-decision decoder","level":3,"score":0.47798842191696167},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4717101752758026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44727545976638794},{"id":"https://openalex.org/C67545415","wikidata":"https://www.wikidata.org/wiki/Q5384218","display_name":"Equalizer","level":3,"score":0.4404953718185425},{"id":"https://openalex.org/C41425797","wikidata":"https://www.wikidata.org/wiki/Q4926640","display_name":"Blind equalization","level":4,"score":0.4108756184577942},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3979123830795288},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39719700813293457},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.19340449571609497},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09764587879180908},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","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/iswcs.2018.8491056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iswcs.2018.8491056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th International Symposium on Wireless Communication Systems (ISWCS)","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":18,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1999032348","https://openalex.org/W2098369756","https://openalex.org/W2098477387","https://openalex.org/W2117103364","https://openalex.org/W2127893101","https://openalex.org/W2150498905","https://openalex.org/W2584943905","https://openalex.org/W2666368276","https://openalex.org/W2736068844","https://openalex.org/W2736402963","https://openalex.org/W2770861014","https://openalex.org/W2785851301","https://openalex.org/W2801951992","https://openalex.org/W2962782499","https://openalex.org/W2964121744","https://openalex.org/W6674855086","https://openalex.org/W6746504796"],"related_works":["https://openalex.org/W2545553786","https://openalex.org/W2349154090","https://openalex.org/W2993703512","https://openalex.org/W2133621247","https://openalex.org/W2277948963","https://openalex.org/W2186363603","https://openalex.org/W2352178434","https://openalex.org/W2384751807","https://openalex.org/W2118910124","https://openalex.org/W2123945883"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,85],"learning":[2,119],"methods":[3],"have":[4],"shown":[5],"significant":[6],"improvements":[7],"in":[8],"communication":[9],"systems.":[10],"In":[11],"this":[12],"paper,":[13],"we":[14,56],"study":[15],"the":[16,20,45,74,84,91,101,106,128],"equalization":[17,40],"problem":[18],"over":[19],"nonlinear":[21,81],"channel":[22,48,78,99],"using":[23],"neural":[24,33,59,66,86],"networks.":[25],"The":[26,121],"joint":[27],"equalizer":[28,109],"and":[29,41,80],"decoder":[30,88],"based":[31,116],"on":[32,117],"networks":[34,60],"are":[35],"proposed":[36,107,122],"to":[37,71,131,141],"realize":[38],"blind":[39],"decoding":[42],"process":[43],"without":[44],"knowledge":[46],"of":[47,62,127],"state":[49],"information":[50],"(CSI).":[51],"Different":[52],"from":[53,77,94],"previous":[54],"methods,":[55],"use":[57],"two":[58],"instead":[61],"one.":[63],"First,":[64],"convolutional":[65],"network":[67,87],"(CNN)":[68],"is":[69],"used":[70],"adaptively":[72],"recover":[73],"transmitted":[75],"signal":[76,93],"impairment":[79],"distortions.":[82],"Then":[83],"(NND)":[89],"decodes":[90],"detected":[92],"CNN":[95,108],"equalizer.":[96],"Under":[97],"various":[98],"conditions,":[100],"experiment":[102],"results":[103],"demonstrate":[104],"that":[105],"achieves":[110],"better":[111],"performance":[112],"than":[113],"other":[114],"solutions":[115],"machine":[118],"methods.":[120],"model":[123,136],"reduces":[124],"about":[125],"2/3":[126],"parameters":[129],"compared":[130],"state-of-the-art":[132],"counterparts.":[133],"Besides,":[134],"our":[135],"can":[137],"be":[138],"easily":[139],"applied":[140],"long":[142],"sequence":[143],"with":[144],"O(n)":[145],"complexity.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}