{"id":"https://openalex.org/W4251164114","doi":"https://doi.org/10.1109/meditcom49071.2021.9647513","title":"Avoiding normalization uncertainties in deep learning architectures for end-to-end communication","display_name":"Avoiding normalization uncertainties in deep learning architectures for end-to-end communication","publication_year":2021,"publication_date":"2021-09-07","ids":{"openalex":"https://openalex.org/W4251164114","doi":"https://doi.org/10.1109/meditcom49071.2021.9647513"},"language":"en","primary_location":{"id":"doi:10.1109/meditcom49071.2021.9647513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/meditcom49071.2021.9647513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)","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/A5003912253","display_name":"Simon Bos","orcid":"https://orcid.org/0000-0003-1807-0202"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Simon Bos","raw_affiliation_strings":["Department of Electrical Engineering, KU Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, KU Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036957045","display_name":"Evgenii Vinogradov","orcid":"https://orcid.org/0000-0002-4156-0317"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Evgenii Vinogradov","raw_affiliation_strings":["Department of Electrical Engineering, KU Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, KU Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028689021","display_name":"Sofie Pollin","orcid":"https://orcid.org/0000-0002-1470-2076"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Sofie Pollin","raw_affiliation_strings":["Department of Electrical Engineering, KU Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, KU Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99464096"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23565353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"485","last_page":"487"},"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9855999946594238,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.982200026512146,"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/normalization","display_name":"Normalization (sociology)","score":0.8658528327941895},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.7829188108444214},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7661772966384888},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.613980233669281},{"id":"https://openalex.org/keywords/slicing","display_name":"Slicing","score":0.5914619565010071},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.578005313873291},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5399103164672852},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5172834396362305},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.39380475878715515},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.32262206077575684}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.8658528327941895},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.7829188108444214},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7661772966384888},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.613980233669281},{"id":"https://openalex.org/C2776190703","wikidata":"https://www.wikidata.org/wiki/Q488148","display_name":"Slicing","level":2,"score":0.5914619565010071},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.578005313873291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5399103164672852},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5172834396362305},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.39380475878715515},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.32262206077575684},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/meditcom49071.2021.9647513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/meditcom49071.2021.9647513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)","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":5,"referenced_works":["https://openalex.org/W2734408173","https://openalex.org/W2736068844","https://openalex.org/W2962902015","https://openalex.org/W2962964572","https://openalex.org/W2968026845"],"related_works":["https://openalex.org/W2393746923","https://openalex.org/W2972496411","https://openalex.org/W3033662781","https://openalex.org/W4239223006","https://openalex.org/W2360869927","https://openalex.org/W2137530048","https://openalex.org/W2050876785","https://openalex.org/W2074642116","https://openalex.org/W4287755480","https://openalex.org/W3113607506"],"abstract_inverted_index":{"Recently,":[0],"deep":[1],"learning":[2,17],"is":[3,24],"considered":[4],"to":[5,35,112],"optimize":[6],"the":[7,29,55,58,81,85,91,97],"end-to-end":[8,59],"performance":[9,115],"of":[10,16,57,99,116],"digital":[11,19],"communication":[12,20],"systems.":[13],"The":[14],"promise":[15],"a":[18,46,77],"scheme":[21,30],"from":[22,62],"data":[23],"attractive,":[25],"since":[26],"this":[27,42,73],"makes":[28],"adaptable":[31],"and":[32,38,52],"precisely":[33],"tunable":[34],"many":[36],"scenarios":[37],"channel":[39],"models.":[40],"In":[41],"paper,":[43],"we":[44,75,104],"analyse":[45],"widely":[47],"used":[48],"neural":[49],"network":[50],"architecture":[51,60,110],"show":[53],"that":[54,107],"training":[56],"suffers":[61],"normalization":[63,86,92,125],"errors":[64],"introduced":[65],"by":[66],"an":[67],"average":[68],"power":[69],"constraint.":[70],"To":[71],"solve":[72],"issue,":[74],"propose":[76],"modified":[78,109],"architecture:":[79],"shifting":[80],"batch":[82,101,122],"slicing":[83],"after":[84],"layer.":[87],"This":[88],"approach":[89],"meets":[90],"constraints":[93,126],"better,":[94],"especially":[95],"in":[96],"case":[98],"small":[100],"sizes.":[102],"Finally,":[103],"experimentally":[105],"demonstrate":[106],"our":[108],"leads":[111],"significantly":[113],"improved":[114],"trained":[117],"models,":[118],"even":[119],"for":[120],"large":[121],"sizes":[123],"where":[124],"are":[127],"more":[128],"easily":[129],"met.":[130]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
