{"id":"https://openalex.org/W4408092530","doi":"https://doi.org/10.1109/ants63515.2024.10898507","title":"Hardware Implementation of Channel Encoder Classification Using Deep Learning","display_name":"Hardware Implementation of Channel Encoder Classification Using Deep Learning","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4408092530","doi":"https://doi.org/10.1109/ants63515.2024.10898507"},"language":"en","primary_location":{"id":"doi:10.1109/ants63515.2024.10898507","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ants63515.2024.10898507","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","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/A5104244968","display_name":"Nayim Ahamed","orcid":null},"institutions":[{"id":"https://openalex.org/I64295750","display_name":"Indian Institute of Technology Indore","ror":"https://ror.org/01hhf7w52","country_code":"IN","type":"education","lineage":["https://openalex.org/I64295750"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Nayim Ahamed","raw_affiliation_strings":["IIT,Department of Electrical Engineering,Indore"],"affiliations":[{"raw_affiliation_string":"IIT,Department of Electrical Engineering,Indore","institution_ids":["https://openalex.org/I64295750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036877094","display_name":"R Swaminathan","orcid":"https://orcid.org/0000-0002-8254-0144"},"institutions":[{"id":"https://openalex.org/I64295750","display_name":"Indian Institute of Technology Indore","ror":"https://ror.org/01hhf7w52","country_code":"IN","type":"education","lineage":["https://openalex.org/I64295750"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R Swaminathan","raw_affiliation_strings":["IIT,Department of Electrical Engineering,Indore"],"affiliations":[{"raw_affiliation_string":"IIT,Department of Electrical Engineering,Indore","institution_ids":["https://openalex.org/I64295750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5104244968"],"corresponding_institution_ids":["https://openalex.org/I64295750"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25894058,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9387000203132629,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9387000203132629,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11034","display_name":"Digital Filter Design and Implementation","score":0.914900004863739,"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/computer-science","display_name":"Computer science","score":0.7615149021148682},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.697735607624054},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.570925772190094},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.5030583739280701},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4650370478630066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4568222165107727},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4180049002170563},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3548993170261383},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.18030643463134766},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.16757822036743164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7615149021148682},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.697735607624054},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.570925772190094},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.5030583739280701},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4650370478630066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4568222165107727},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4180049002170563},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3548993170261383},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.18030643463134766},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.16757822036743164}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ants63515.2024.10898507","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ants63515.2024.10898507","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","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":0,"referenced_works":[],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W4205302943","https://openalex.org/W2561132942","https://openalex.org/W2611989081","https://openalex.org/W3155418658","https://openalex.org/W2363440576"],"abstract_inverted_index":{"Channel":[0],"encoders":[1,66],"in":[2,22,29,203,222,246],"digital":[3],"communication":[4,32,249],"systems":[5],"are":[6,186],"crucial":[7],"for":[8,49,108,115,134],"mitigating":[9],"random":[10],"errors":[11],"introduced":[12],"by":[13,155],"noisy":[14],"channels.":[15,92],"While":[16],"encoder":[17],"information":[18],"is":[19,26],"usually":[20],"accessible":[21],"cooperative":[23],"scenarios,":[24],"it":[25],"often":[27],"unavailable":[28],"non-cooperative":[30],"military":[31],"systems.":[33],"In":[34],"this":[35],"paper,":[36],"we":[37,193],"present":[38],"a":[39,97,171],"hybrid":[40,216],"convolutional":[41,65],"neural":[42],"network":[43],"(CNN)-support":[44],"vector":[45],"machine":[46],"(SVM)":[47],"model":[48,95,130,218],"the":[50,79,157,166,183,189,200,204,235],"blind":[51],"identification":[52],"of":[53,100,122,224,239],"forward":[54],"error":[55],"correction":[56],"(FEC)":[57],"encoders.":[58],"Our":[59],"work":[60],"focuses":[61],"on":[62],"classifying":[63],"different":[64],"with":[67,119,165,188,199],"rates":[68],"$1":[69,75,123],"/":[70,72,76],"2,1":[71],"3$,":[73],"and":[74,89,110,146,211,237],"4$":[77],"from":[78],"message":[80],"signals":[81],"received":[82],"over":[83],"additive":[84],"white":[85],"Gaussian":[86],"noise":[87],"(AWGN)":[88],"Rayleigh":[90,116,147,207],"fading":[91,117,148,208],"The":[93],"proposed":[94,215],"surpasses":[96],"classification":[98],"accuracy":[99,133],"95%":[101],"at":[102,111,227],"2":[103],"dB":[104,113,140,229],"signal-to-noise":[105],"ratio":[106],"(SNR)":[107],"AWGN":[109,145],"5":[112,228],"SNR":[114,141,230],"channels":[118],"input":[120,136],"lengths":[121,137],"6,":[124],"3":[125],"8":[126],"4$.":[127],"Additionally,":[128],"our":[129,153,196,214,240],"achieves":[131],"100%":[132],"all":[135],"beyond":[138],"10":[139],"level":[142],"under":[143,206],"both":[144],"channel":[149,209],"conditions.":[150],"We":[151],"validate":[152],"findings":[154],"comparing":[156],"results":[158,185,233],"obtained":[159],"using":[160],"datasets":[161,168],"generated":[162,169],"through":[163],"simulations":[164,190],"real-time":[167,184],"via":[170],"GNU":[172],"Radio-based":[173],"universal":[174],"software":[175],"radio":[176],"peripheral":[177],"(USRP)":[178],"B210":[179],"device,":[180],"revealing":[181],"that":[182,213],"comparable":[187],"results.":[191],"Moreover,":[192],"have":[194],"compared":[195],"model\u2019s":[197],"performance":[198,245],"existing":[201],"models":[202],"literature":[205],"condition":[210],"observed":[212],"CNN-SVM":[217],"significantly":[219],"outperforms":[220],"them":[221],"terms":[223],"accuracy,":[225],"particularly":[226],"level.":[231],"These":[232],"highlight":[234],"effectiveness":[236],"robustness":[238],"model,":[241],"demonstrating":[242],"its":[243],"superior":[244],"practical":[247],"wireless":[248],"scenarios.":[250]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}