{"id":"https://openalex.org/W2549981421","doi":"https://doi.org/10.1109/ijcnn.2016.7727329","title":"An energy efficient decoding scheme for nonlinear MIMO-OFDM network using reservoir computing","display_name":"An energy efficient decoding scheme for nonlinear MIMO-OFDM network using reservoir computing","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2549981421","doi":"https://doi.org/10.1109/ijcnn.2016.7727329","mag":"2549981421"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5078588560","display_name":"Susanna Mosleh","orcid":"https://orcid.org/0000-0003-3813-4971"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Susanna Mosleh","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, US"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, US","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081895279","display_name":"Cenk \u015eahin","orcid":null},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cenk Sahin","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, US"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, US","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027237940","display_name":"Lingjia Liu","orcid":"https://orcid.org/0000-0003-1915-1784"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lingjia Liu","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, US"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, US","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101721176","display_name":"Ren Zheng","orcid":"https://orcid.org/0000-0002-4147-9359"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R.Y. Zheng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Missouri University of Science and Technology, MO, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Missouri University of Science and Technology, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102822513","display_name":"Yi Yang","orcid":"https://orcid.org/0009-0002-1682-1957"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Yang","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, US"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, US","institution_ids":["https://openalex.org/I146416000"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5078588560"],"corresponding_institution_ids":["https://openalex.org/I146416000"],"apc_list":null,"apc_paid":null,"fwci":3.1104,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.9324904,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1166","last_page":"1173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","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/T12611","display_name":"Neural Networks and Reservoir Computing","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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9890000224113464,"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/T10232","display_name":"Optical Network Technologies","score":0.9876999855041504,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/orthogonal-frequency-division-multiplexing","display_name":"Orthogonal frequency-division multiplexing","score":0.7399117946624756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7103101015090942},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.6727708578109741},{"id":"https://openalex.org/keywords/echo-state-network","display_name":"Echo state network","score":0.6116456985473633},{"id":"https://openalex.org/keywords/mimo-ofdm","display_name":"MIMO-OFDM","score":0.6075367331504822},{"id":"https://openalex.org/keywords/reservoir-computing","display_name":"Reservoir computing","score":0.6010668277740479},{"id":"https://openalex.org/keywords/nonlinear-distortion","display_name":"Nonlinear distortion","score":0.548423171043396},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5141744613647461},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.4995460510253906},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.49752476811408997},{"id":"https://openalex.org/keywords/transmitter","display_name":"Transmitter","score":0.48435577750205994},{"id":"https://openalex.org/keywords/multiplexing","display_name":"Multiplexing","score":0.43168362975120544},{"id":"https://openalex.org/keywords/bit-error-rate","display_name":"Bit error rate","score":0.43045079708099365},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4275197386741638},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4161871075630188},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3635367751121521},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.34870103001594543},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.34692108631134033},{"id":"https://openalex.org/keywords/amplifier","display_name":"Amplifier","score":0.2789098024368286},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1649024784564972},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16218969225883484},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15418824553489685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1066955029964447}],"concepts":[{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.7399117946624756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7103101015090942},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.6727708578109741},{"id":"https://openalex.org/C172025690","wikidata":"https://www.wikidata.org/wiki/Q5332763","display_name":"Echo state network","level":4,"score":0.6116456985473633},{"id":"https://openalex.org/C130946814","wikidata":"https://www.wikidata.org/wiki/Q5988271","display_name":"MIMO-OFDM","level":4,"score":0.6075367331504822},{"id":"https://openalex.org/C135796866","wikidata":"https://www.wikidata.org/wiki/Q7315328","display_name":"Reservoir computing","level":4,"score":0.6010668277740479},{"id":"https://openalex.org/C173413354","wikidata":"https://www.wikidata.org/wiki/Q7049470","display_name":"Nonlinear distortion","level":4,"score":0.548423171043396},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5141744613647461},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.4995460510253906},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.49752476811408997},{"id":"https://openalex.org/C47798520","wikidata":"https://www.wikidata.org/wiki/Q190157","display_name":"Transmitter","level":3,"score":0.48435577750205994},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.43168362975120544},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.43045079708099365},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4275197386741638},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4161871075630188},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3635367751121521},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.34870103001594543},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.34692108631134033},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.2789098024368286},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1649024784564972},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16218969225883484},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15418824553489685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1066955029964447},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1609941950","https://openalex.org/W1667165204","https://openalex.org/W1667950888","https://openalex.org/W1969271919","https://openalex.org/W2054217036","https://openalex.org/W2061056596","https://openalex.org/W2101397645","https://openalex.org/W2103179919","https://openalex.org/W2118706537","https://openalex.org/W2119755184","https://openalex.org/W2121051729","https://openalex.org/W2134342468","https://openalex.org/W2140577326","https://openalex.org/W2149587304","https://openalex.org/W2159682675","https://openalex.org/W2163377067","https://openalex.org/W2294132199","https://openalex.org/W2398309275","https://openalex.org/W7034522702"],"related_works":["https://openalex.org/W57315087","https://openalex.org/W2010974764","https://openalex.org/W4386848428","https://openalex.org/W4205631599","https://openalex.org/W2021379535","https://openalex.org/W2020067398","https://openalex.org/W2967225774","https://openalex.org/W2903992663","https://openalex.org/W4237814686","https://openalex.org/W2997427060"],"abstract_inverted_index":{"Reservoir":[0],"computing":[1],"(RC)":[2],"is":[3,35,56,109],"attracting":[4],"widespread":[5],"attention":[6],"in":[7,46],"several":[8],"signal":[9,77],"processing":[10],"domains":[11],"owing":[12],"to":[13,58,70],"its":[14],"nonlinear":[15,90,152,165],"stateful":[16],"computation.":[17],"It":[18,34],"deals":[19],"particularly":[20],"well":[21],"with":[22],"time-series":[23,138],"prediction":[24],"tasks":[25],"and":[26,150],"reduces":[27],"training":[28],"complexity":[29],"over":[30],"recurrent":[31,132],"neural":[32,133],"networks.":[33],"also":[36],"suitable":[37],"for":[38,85,146,158],"hardware":[39],"implementation":[40],"whereby":[41],"device":[42],"physics":[43],"are":[44,130],"utilized":[45],"performing":[47],"data":[48],"processing.":[49],"In":[50,112],"this":[51,102,113],"paper,":[52,114],"the":[53,71,75,87,94,98,159,164,170],"RC":[54],"concept":[55],"applied":[57],"modeling":[59,148],"a":[60,117,144],"Multiple-Input":[61],"Multiple-Output":[62],"Orthogonal":[63],"Frequency":[64],"Division":[65],"Multiplexing":[66],"(MIMO-OFDM)":[67],"system.":[68],"Due":[69],"harsh":[72],"propagation":[73],"environment,":[74],"transmitted":[76],"undergoes":[78],"severe":[79],"distortion":[80,91],"that":[81,135,169],"must":[82],"be":[83],"compensated":[84],"at":[86,97],"receiver.":[88],"The":[89],"introduced":[92,171],"by":[93],"power":[95],"amplifier":[96],"transmitter":[99],"further":[100],"complicates":[101],"process.":[103],"An":[104],"effective":[105],"channel":[106,119,172,177],"estimation":[107,120,178],"scheme":[108,121],"therefore":[110],"required.":[111],"we":[115],"introduce":[116],"MIMO-OFDM":[118,166],"utilizing":[122],"Echo":[123,127],"State":[124,128],"Network":[125],"(ESN).":[126],"Networks":[129],"powerful":[131],"networks":[134],"can":[136],"predict":[137],"very":[139],"well.":[140],"They":[141],"acts":[142],"as":[143],"black-box":[145],"system":[147,167],"purposes":[149],"models":[151],"dynamic":[153],"systems":[154],"efficiently.":[155],"Simulation":[156],"results":[157],"bit":[160],"error":[161],"rate":[162],"of":[163],"show":[168],"estimator":[173],"outperforms":[174],"commonly":[175],"used":[176],"schemes.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}