{"id":"https://openalex.org/W4280581475","doi":"https://doi.org/10.1109/wcnc51071.2022.9771761","title":"PR-SRNN: Constellation Image Analysis Assisted Channel Estimation with 1 DMRS","display_name":"PR-SRNN: Constellation Image Analysis Assisted Channel Estimation with 1 DMRS","publication_year":2022,"publication_date":"2022-04-10","ids":{"openalex":"https://openalex.org/W4280581475","doi":"https://doi.org/10.1109/wcnc51071.2022.9771761"},"language":"en","primary_location":{"id":"doi:10.1109/wcnc51071.2022.9771761","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcnc51071.2022.9771761","pdf_url":null,"source":{"id":"https://openalex.org/S4363607776","display_name":"2022 IEEE Wireless Communications and Networking Conference (WCNC)","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":"2022 IEEE Wireless Communications and Networking Conference (WCNC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101591872","display_name":"Wenliang Qi","orcid":"https://orcid.org/0000-0002-0095-7596"},"institutions":[{"id":"https://openalex.org/I4210099903","display_name":"Nokia (China)","ror":"https://ror.org/01607kg94","country_code":"CN","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210099903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenliang Qi","raw_affiliation_strings":["Nokia Bell Labs China,Shanghai,China","Nokia Bell Labs China, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs China,Shanghai,China","institution_ids":["https://openalex.org/I4210099903"]},{"raw_affiliation_string":"Nokia Bell Labs China, Shanghai, China","institution_ids":["https://openalex.org/I4210099903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066009762","display_name":"Chenhui Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099903","display_name":"Nokia (China)","ror":"https://ror.org/01607kg94","country_code":"CN","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210099903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenhui Ye","raw_affiliation_strings":["Nokia Bell Labs China,Shanghai,China","Nokia Bell Labs China, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs China,Shanghai,China","institution_ids":["https://openalex.org/I4210099903"]},{"raw_affiliation_string":"Nokia Bell Labs China, Shanghai, China","institution_ids":["https://openalex.org/I4210099903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101698318","display_name":"Zhiyuan Wu","orcid":"https://orcid.org/0000-0003-4746-2168"},"institutions":[{"id":"https://openalex.org/I4210099903","display_name":"Nokia (China)","ror":"https://ror.org/01607kg94","country_code":"CN","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210099903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Wu","raw_affiliation_strings":["Nokia Bell Labs China,Shanghai,China","Nokia Bell Labs China, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs China,Shanghai,China","institution_ids":["https://openalex.org/I4210099903"]},{"raw_affiliation_string":"Nokia Bell Labs China, Shanghai, China","institution_ids":["https://openalex.org/I4210099903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110816852","display_name":"Ruiling Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099903","display_name":"Nokia (China)","ror":"https://ror.org/01607kg94","country_code":"CN","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210099903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiling Zhao","raw_affiliation_strings":["Nokia Bell Labs China,Shanghai,China","Nokia Bell Labs China, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs China,Shanghai,China","institution_ids":["https://openalex.org/I4210099903"]},{"raw_affiliation_string":"Nokia Bell Labs China, Shanghai, China","institution_ids":["https://openalex.org/I4210099903"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003942874","display_name":"Dani Korpi","orcid":"https://orcid.org/0000-0003-3460-7436"},"institutions":[{"id":"https://openalex.org/I2738502077","display_name":"Nokia (Finland)","ror":"https://ror.org/04pkc8m17","country_code":"FI","type":"company","lineage":["https://openalex.org/I2738502077"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Dani Korpi","raw_affiliation_strings":["Nokia Bell Labs Finland,Espoo,Finland","Nokia Bell Labs Finland, Espoo, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs Finland,Espoo,Finland","institution_ids":["https://openalex.org/I2738502077"]},{"raw_affiliation_string":"Nokia Bell Labs Finland, Espoo, Finland","institution_ids":["https://openalex.org/I2738502077"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1677","last_page":"1682"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11946","display_name":"Antenna Design and Optimization","score":0.9934999942779541,"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"}},"topics":[{"id":"https://openalex.org/T11946","display_name":"Antenna Design and Optimization","score":0.9934999942779541,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9840999841690063,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9812999963760376,"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":0.7908975481987},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.566501259803772},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5376687049865723},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.5053423047065735},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.4961720407009125},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44616666436195374},{"id":"https://openalex.org/keywords/doppler-effect","display_name":"Doppler effect","score":0.43558967113494873},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41862958669662476},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41470301151275635},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35691606998443604},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32795828580856323},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.31901031732559204}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7908975481987},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.566501259803772},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5376687049865723},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.5053423047065735},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.4961720407009125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44616666436195374},{"id":"https://openalex.org/C142757262","wikidata":"https://www.wikidata.org/wiki/Q76436","display_name":"Doppler effect","level":2,"score":0.43558967113494873},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41862958669662476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41470301151275635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35691606998443604},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32795828580856323},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.31901031732559204},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcnc51071.2022.9771761","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcnc51071.2022.9771761","pdf_url":null,"source":{"id":"https://openalex.org/S4363607776","display_name":"2022 IEEE Wireless Communications and Networking Conference (WCNC)","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":"2022 IEEE Wireless Communications and Networking Conference (WCNC)","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/W2376969857","https://openalex.org/W207732638","https://openalex.org/W2801592279","https://openalex.org/W4252788403","https://openalex.org/W2171869298","https://openalex.org/W2034040913","https://openalex.org/W2257001073","https://openalex.org/W1992602584","https://openalex.org/W2549306799","https://openalex.org/W1985266503"],"abstract_inverted_index":{"The":[0,71,94,159],"time-varying":[1],"and":[2,78,123,169,213,222],"non-stationary":[3],"channel":[4,30,112,167,200],"characteristics":[5],"caused":[6],"by":[7,64,80],"high":[8],"Doppler":[9,45,74,121,181],"effects":[10,75,122,182,244],"is":[11,41,62,99,133,148,240],"a":[12,25,33,103,141,234],"significant":[13],"challenge":[14],"for":[15,242],"modern":[16],"wireless":[17],"communication":[18],"systems.":[19],"Aiming":[20],"at":[21],"the":[22,65,90,111,134,151,184,217],"high-speed":[23,69],"scenarios,":[24],"constellation":[26,92,146],"image":[27],"analysis":[28,157],"aided":[29],"estimation":[31,113],"using":[32],"hybrid":[34],"neural":[35,85],"network":[36,86],"(NN)":[37],"structure,":[38],"named":[39],"PR-SRNN,":[40],"proposed":[42,66,225],"to":[43,137,150,249],"combat":[44],"effects.":[46],"Only":[47],"1":[48],"demodulation":[49],"reference":[50],"signal":[51],"(DMRS)":[52],"pilot,":[53],"rather":[54],"than":[55],"multiple":[56],"pilots":[57],"as":[58,155,233],"in":[59,68,114,209,229],"previous":[60],"reports,":[61],"needed":[63],"PR-SRNN":[67,174,221,239],"scenarios.":[70],"impacts":[72],"from":[73],"are":[76,129],"analyzed":[77],"compensated":[79],"an":[81],"intelligent":[82],"pattern":[83,142],"recognition":[84,143],"(PRNN)":[87],"based":[88,162],"on":[89,145,163],"contaminated":[91],"images.":[93],"output":[95],"layer":[96],"of":[97,180,191,211],"PRNN":[98],"then":[100],"merged":[101],"with":[102,199],"super":[104,192],"resolution":[105,193],"NN":[106,144],"(SRNN)":[107],"which":[108,227],"preliminarily":[109],"reconstructs":[110],"frequency":[115],"domain.":[116],"Adaptive":[117],"features":[118],"learning":[119],"against":[120,126,177],"synergic":[124],"compensation":[125],"multipath":[127],"fading":[128],"learnt":[130],"jointly.":[131],"It":[132],"first":[135],"time":[136],"our":[138,223],"knowledge":[139],"that":[140,173,238],"images":[147],"introduced":[149],"physical":[152],"layer,":[153],"functioning":[154],"expert-like":[156],"system.":[158],"simulation":[160],"results":[161],"both":[164],"3GPP":[165],"statistical":[166],"models":[168],"ray":[170],"tracing":[171],"show":[172],"exhibits":[175],"robustness":[176],"diverse":[178],"degrees":[179],"beyond":[183],"pretrained":[185],"scope.":[186],"Amongst":[187],"different":[188],"framework":[189],"candidates":[190],"(SR)":[194],"NNs,":[195],"residual":[196],"convolution":[197],"SRNN":[198],"attention":[201],"has":[202],"been":[203],"selected":[204],"regarding":[205],"its":[206],"performance":[207],"superiority":[208],"terms":[210],"loss":[212],"convergence":[214],"speed.":[215],"Furthermore,":[216],"cross":[218],"validation":[219],"between":[220],"previously":[224],"SubSRNN":[226],"takes":[228],"extra":[230,246],"semantic":[231],"information":[232,248],"2<sup>nd</sup>":[235],"input":[236],"proves":[237],"effective":[241],"Dopplers":[243],"without":[245],"side":[247],"be":[250],"reported.":[251]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}