{"id":"https://openalex.org/W3046125876","doi":"https://doi.org/10.1109/icc40277.2020.9149030","title":"Bilinear Convolutional Auto-encoder based Pilot-free End-to-end Communication Systems","display_name":"Bilinear Convolutional Auto-encoder based Pilot-free End-to-end Communication Systems","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3046125876","doi":"https://doi.org/10.1109/icc40277.2020.9149030","mag":"3046125876"},"language":"en","primary_location":{"id":"doi:10.1109/icc40277.2020.9149030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc40277.2020.9149030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","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/A5100427161","display_name":"Hao Ye","orcid":"https://orcid.org/0000-0003-1544-1768"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hao Ye","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039289964","display_name":"Geoffrey Ye Li","orcid":"https://orcid.org/0000-0002-7894-2415"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Geoffrey Ye Li","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070867959","display_name":"Biing\u2010Hwang Juang","orcid":"https://orcid.org/0000-0002-5773-5679"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Biing-Hwang Fred Juang","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100427161"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.7954,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.78308821,"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":"1","last_page":"6"},"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":0.9915000200271606,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.7881290912628174},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.7132383584976196},{"id":"https://openalex.org/keywords/transmitter","display_name":"Transmitter","score":0.6998481154441833},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6267454624176025},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5886312127113342},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5739936828613281},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5430258512496948},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5126485228538513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4602109491825104},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.42987504601478577},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3232365846633911},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3204818367958069},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20622089505195618},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.17179960012435913}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7881290912628174},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.7132383584976196},{"id":"https://openalex.org/C47798520","wikidata":"https://www.wikidata.org/wiki/Q190157","display_name":"Transmitter","level":3,"score":0.6998481154441833},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6267454624176025},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5886312127113342},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5739936828613281},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5430258512496948},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5126485228538513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4602109491825104},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.42987504601478577},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3232365846633911},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3204818367958069},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20622089505195618},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.17179960012435913},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc40277.2020.9149030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc40277.2020.9149030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","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":13,"referenced_works":["https://openalex.org/W1991133427","https://openalex.org/W2104657103","https://openalex.org/W2147800946","https://openalex.org/W2734408173","https://openalex.org/W2736068844","https://openalex.org/W2889153869","https://openalex.org/W2962964572","https://openalex.org/W2964198392","https://openalex.org/W2968026845","https://openalex.org/W2970647284","https://openalex.org/W4297824792","https://openalex.org/W6749474472","https://openalex.org/W6999787859"],"related_works":["https://openalex.org/W2355663289","https://openalex.org/W2106913410","https://openalex.org/W4380372336","https://openalex.org/W2354248671","https://openalex.org/W3179968364","https://openalex.org/W2359134391","https://openalex.org/W2594116857","https://openalex.org/W2947628004","https://openalex.org/W2935229758","https://openalex.org/W2059045613"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,20,55],"learning":[2],"based":[3],"end-to-end":[4,26,46],"communication":[5],"systems":[6],"have":[7],"been":[8],"developed,":[9],"where":[10],"both":[11],"the":[12,15,36,39,45,82,85,90,99,117,135,141,154],"transmitter":[13],"and":[14,24,63,73,109,131,165],"receiver":[16,100],"are":[17,122],"represented":[18],"as":[19,52],"neural":[21],"networks":[22],"(DNN)":[23],"an":[25,59],"loss":[27],"is":[28],"optimized":[29],"directly.":[30],"In":[31,97],"this":[32,50],"paper,":[33],"we":[34],"address":[35,89],"effects":[37,92],"of":[38,70,76],"more":[40],"general":[41],"wireless":[42,160],"channels":[43,164],"to":[44,79,88,139],"framework.":[47],"We":[48],"formulate":[49],"problem":[51],"training":[53,66],"a":[54,65,128,149],"auto-encoder":[56,86],"system":[57],"with":[58,68,124,153],"adversarial":[60],"convolutional":[61],"layer":[62],"propose":[64],"procedure":[67],"mini-batches":[69],"input":[71,143],"samples":[72],"channels.":[74,169],"Instead":[75],"using":[77],"pilots":[78],"explicitly":[80],"estimate":[81],"unknown":[83],"channel,":[84],"learns":[87],"channel":[91,106,118],"without":[93],"any":[94],"pilot":[95],"information.":[96],"particular,":[98],"contains":[101],"two":[102],"modules,":[103],"designed":[104],"for":[105],"information":[107,119],"extraction":[108,120],"data":[110,136],"recovery,":[111],"respectively.":[112],"The":[113,145],"features":[114],"obtained":[115],"from":[116],"module":[121,138],"combined":[123],"received":[125],"signals":[126],"by":[127,134],"bilinear":[129],"production":[130],"then":[132],"processed":[133],"recovery":[137],"reconstruct":[140],"original":[142],"data.":[144],"experimental":[146],"results":[147],"show":[148],"performance":[150],"improvement":[151],"compared":[152],"traditional":[155],"methods":[156],"in":[157],"commonly":[158],"seen":[159],"channels,":[161],"including":[162],"frequency-selective":[163],"multi-input":[166],"multi-output":[167],"(MIMO)":[168]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}