{"id":"https://openalex.org/W4290996380","doi":"https://doi.org/10.1109/icc45855.2022.9839215","title":"ProductAE: Toward Training Larger Channel Codes based on Neural Product Codes","display_name":"ProductAE: Toward Training Larger Channel Codes based on Neural Product Codes","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4290996380","doi":"https://doi.org/10.1109/icc45855.2022.9839215"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9839215","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839215","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","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/A5088051341","display_name":"Mohammad Vahid Jamali","orcid":"https://orcid.org/0000-0002-5007-0221"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Vahid Jamali","raw_affiliation_strings":["University of Michigan,Department of Electrical Engineering and Computer Science,Ann Arbor","Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan,Department of Electrical Engineering and Computer Science,Ann Arbor","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027932348","display_name":"Hamid Saber","orcid":"https://orcid.org/0000-0002-4418-5866"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hamid Saber","raw_affiliation_strings":["Samsung Semiconductor, Inc.,SOC Lab","SOC Lab, Samsung Semiconductor, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Semiconductor, Inc.,SOC Lab","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"SOC Lab, Samsung Semiconductor, Inc","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074021248","display_name":"Homayoon Hatami","orcid":"https://orcid.org/0000-0001-6217-3415"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Homayoon Hatami","raw_affiliation_strings":["Samsung Semiconductor, Inc.,SOC Lab","SOC Lab, Samsung Semiconductor, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Semiconductor, Inc.,SOC Lab","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"SOC Lab, Samsung Semiconductor, Inc","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046180915","display_name":"Jung Hyun Bae","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jung Hyun Bae","raw_affiliation_strings":["Samsung Semiconductor, Inc.,SOC Lab","SOC Lab, Samsung Semiconductor, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Semiconductor, Inc.,SOC Lab","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"SOC Lab, Samsung Semiconductor, Inc","institution_ids":["https://openalex.org/I2250650973"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.3541,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.97634855,"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":"3898","last_page":"3903"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9994000196456909,"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":0.9987999796867371,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9918000102043152,"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/encoder","display_name":"Encoder","score":0.6586329936981201},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6419898271560669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6148992776870728},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5996884703636169},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5707610249519348},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5451672077178955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5062886476516724},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49241673946380615},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4581831991672516},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4539865553379059},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4175080358982086},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39615941047668457},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34552937746047974},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17216083407402039},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12280595302581787},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10484617948532104}],"concepts":[{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6586329936981201},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6419898271560669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6148992776870728},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5996884703636169},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5707610249519348},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5451672077178955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5062886476516724},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49241673946380615},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4581831991672516},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4539865553379059},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4175080358982086},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39615941047668457},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34552937746047974},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17216083407402039},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12280595302581787},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10484617948532104},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9839215","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839215","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","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":29,"referenced_works":["https://openalex.org/W1995875735","https://openalex.org/W2121606987","https://openalex.org/W2128765501","https://openalex.org/W2143781601","https://openalex.org/W2150498905","https://openalex.org/W2167657277","https://openalex.org/W2463903161","https://openalex.org/W2584943905","https://openalex.org/W2589785008","https://openalex.org/W2666368276","https://openalex.org/W2734408173","https://openalex.org/W2770861014","https://openalex.org/W2889372359","https://openalex.org/W2898421447","https://openalex.org/W2963120184","https://openalex.org/W2963408536","https://openalex.org/W2963622214","https://openalex.org/W2964070430","https://openalex.org/W2970647284","https://openalex.org/W2970982053","https://openalex.org/W3005799687","https://openalex.org/W3015658753","https://openalex.org/W3080746295","https://openalex.org/W3198668109","https://openalex.org/W4252713891","https://openalex.org/W4287019342","https://openalex.org/W4290996444","https://openalex.org/W6767478059","https://openalex.org/W6796904836"],"related_works":["https://openalex.org/W4296209631","https://openalex.org/W2561617217","https://openalex.org/W2025378473","https://openalex.org/W4390516098","https://openalex.org/W2161474341","https://openalex.org/W2355801475","https://openalex.org/W1968289971","https://openalex.org/W4300588357","https://openalex.org/W2163885456","https://openalex.org/W4242191701"],"abstract_inverted_index":{"There":[0],"have":[1],"been":[2],"significant":[3,202],"research":[4],"activities":[5],"in":[6,25,50],"recent":[7],"years":[8],"to":[9,32,55,251],"automate":[10],"the":[11,22,48,51,85,104,126,153,248],"design":[12,33,252],"of":[13,47,75,87,123,135,207,214,221],"channel":[14,26,39,90,262],"encoders":[15,93,149],"and":[16,34,94,110,128,138,150,165,187,217,242,255],"decoders":[17,151],"via":[18,41],"deep":[19,42],"learning.":[20],"Due":[21],"dimensionality":[23],"challenge":[24],"coding,":[27],"it":[28],"is":[29,247],"prohibitively":[30],"complex":[31],"train":[35],"relatively":[36,56,88],"large":[37,89,113,132,261],"neural":[38,114,133,148],"codes":[40,58,91,115,226],"learning":[43],"techniques.":[44],"Consequently,":[45],"most":[46],"results":[49,200,234],"literature":[52],"are":[53],"limited":[54],"short":[57],"having":[59],"less":[60],"than":[61],"100":[62],"information":[63],"bits.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68,141],"construct":[69],"ProductAEs,":[70],"a":[71,97,131,143,212,218,256],"computationally":[72],"efficient":[73],"family":[74],"deep-learning":[76],"driven":[77],"(encoder,":[78],"decoder)":[79],"pairs,":[80],"that":[81,145,176],"aim":[82],"at":[83],"enabling":[84],"training":[86,99,125,147,199,260],"(both":[92],"decoders)":[95],"with":[96],"manageable":[98],"complexity.":[100],"We":[101],"build":[102],"upon":[103],"ideas":[105],"from":[106],"classical":[107,244],"product":[108,253],"codes,":[109],"propose":[111],"constructing":[112],"using":[116],"smaller":[117],"code":[118,134,154,213,220],"components.":[119],"More":[120],"specifically,":[121],"instead":[122],"directly":[124],"encoder":[127],"decoder":[129],"for":[130,152,211],"dimension":[136],"k":[137,188,192],"blocklength":[139],"n,":[140],"provide":[142],"framework":[144],"requires":[146],"parameters":[155,215,222],"(n":[156,166],"<inf":[157,161,167,171,178,182,189,193],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[158,162,168,172,179,183,190,194],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</inf>":[159,163,180,191],",k":[160,170],")":[164,174],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</inf>":[169,173,184,195],"such":[175],"n":[177,181,186],"=":[185,196],"k.":[197],"Our":[198],"show":[201],"gains,":[203],"over":[204,224,238],"all":[205],"ranges":[206],"signal-to-noise":[208],"ratio":[209],"(SNR),":[210],"(225,100)":[216],"moderate-length":[219],"(441,196),":[223],"polar":[225],"under":[227],"successive":[228],"cancellation":[229],"(SC)":[230],"decoder.":[231],"Moreover,":[232],"our":[233],"demonstrate":[235],"meaningful":[236],"gains":[237],"Turbo":[239],"Autoencoder":[240],"(TurboAE)":[241],"state-of-the-art":[243],"codes.":[245,263],"This":[246],"first":[249],"work":[250,258],"autoencoders":[254],"pioneering":[257],"on":[259]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}