{"id":"https://openalex.org/W3082926577","doi":"https://doi.org/10.1109/twc.2021.3100148","title":"Deep Residual Learning for Channel Estimation in Intelligent Reflecting Surface-Assisted Multi-User Communications","display_name":"Deep Residual Learning for Channel Estimation in Intelligent Reflecting Surface-Assisted Multi-User Communications","publication_year":2021,"publication_date":"2021-08-03","ids":{"openalex":"https://openalex.org/W3082926577","doi":"https://doi.org/10.1109/twc.2021.3100148","mag":"3082926577"},"language":"en","primary_location":{"id":"doi:10.1109/twc.2021.3100148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2021.3100148","pdf_url":null,"source":{"id":"https://openalex.org/S63459445","display_name":"IEEE Transactions on Wireless Communications","issn_l":"1536-1276","issn":["1536-1276","1558-2248"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Wireless Communications","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2009.01423","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chang Liu","orcid":"https://orcid.org/0000-0003-4959-7541"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU","CN"],"is_corresponding":true,"raw_author_name":"Chang Liu","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China","School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xuemeng Liu","orcid":"https://orcid.org/0000-0002-4527-0173"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xuemeng Liu","raw_affiliation_strings":["School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Derrick Wing Kwan Ng","orcid":"https://orcid.org/0000-0001-6400-712X"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Derrick Wing Kwan Ng","raw_affiliation_strings":["School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jinhong Yuan","orcid":"https://orcid.org/0000-0002-5794-493X"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jinhong Yuan","raw_affiliation_strings":["School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711","https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":17.9117,"has_fulltext":false,"cited_by_count":225,"citation_normalized_percentile":{"value":0.99640411,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"21","issue":"2","first_page":"898","last_page":"912"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9980999827384949,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9980999827384949,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.00019999999494757503,"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/T10851","display_name":"Optical Wireless Communication Technologies","score":0.00019999999494757503,"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/estimator","display_name":"Estimator","score":0.7839000225067139},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6644999980926514},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6504999995231628},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.48820000886917114},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47859999537467957},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.474700003862381},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4627000093460083},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.3993000090122223},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.385699987411499}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7839000225067139},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7491000294685364},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6644999980926514},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6504999995231628},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.48820000886917114},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47859999537467957},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.474700003862381},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46619999408721924},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4627000093460083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4512999951839447},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.3993000090122223},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.385699987411499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3716000020503998},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.3644999861717224},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C2781089630","wikidata":"https://www.wikidata.org/wiki/Q21856745","display_name":"Realization (probability)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3167000114917755},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C101765175","wikidata":"https://www.wikidata.org/wiki/Q577764","display_name":"Communications system","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/twc.2021.3100148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2021.3100148","pdf_url":null,"source":{"id":"https://openalex.org/S63459445","display_name":"IEEE Transactions on Wireless Communications","issn_l":"1536-1276","issn":["1536-1276","1558-2248"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Wireless Communications","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2009.01423","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.01423","pdf_url":"https://arxiv.org/pdf/2009.01423","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2009.01423","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.01423","pdf_url":"https://arxiv.org/pdf/2009.01423","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1932847118","https://openalex.org/W1997834106","https://openalex.org/W2100495367","https://openalex.org/W2130134073","https://openalex.org/W2137983211","https://openalex.org/W2194775991","https://openalex.org/W2508457857","https://openalex.org/W2536076834","https://openalex.org/W2556347567","https://openalex.org/W2608727628","https://openalex.org/W2738538347","https://openalex.org/W2805166665","https://openalex.org/W2919115771","https://openalex.org/W2920582597","https://openalex.org/W2937693915","https://openalex.org/W2950077417","https://openalex.org/W2963121727","https://openalex.org/W2963290405","https://openalex.org/W2963889719","https://openalex.org/W2966910701","https://openalex.org/W2969424089","https://openalex.org/W2970670564","https://openalex.org/W2971912794","https://openalex.org/W2975790550","https://openalex.org/W2981792785","https://openalex.org/W2990747873","https://openalex.org/W3001613668","https://openalex.org/W3004201425","https://openalex.org/W3005476696","https://openalex.org/W3006762012","https://openalex.org/W3010384738","https://openalex.org/W3010695123","https://openalex.org/W3011747750","https://openalex.org/W3015419519","https://openalex.org/W3016081664","https://openalex.org/W3021024154","https://openalex.org/W3021335732","https://openalex.org/W3027118737","https://openalex.org/W3034448035","https://openalex.org/W3035217884","https://openalex.org/W3035386068","https://openalex.org/W3036185781","https://openalex.org/W3039402952","https://openalex.org/W3041653465","https://openalex.org/W3045793887","https://openalex.org/W3135424183","https://openalex.org/W3187793142","https://openalex.org/W4298227433","https://openalex.org/W6682889407","https://openalex.org/W6762113363","https://openalex.org/W6770412359","https://openalex.org/W6780672867"],"related_works":["https://openalex.org/W2106362003","https://openalex.org/W1828978430","https://openalex.org/W1899566178","https://openalex.org/W4224217363","https://openalex.org/W4226198870","https://openalex.org/W2089752072","https://openalex.org/W2096219345","https://openalex.org/W2737812849","https://openalex.org/W3100425064","https://openalex.org/W4226372654"],"abstract_inverted_index":{"Channel":[0],"estimation":[1,68,77,116,153,208],"is":[2,56,126,148,169,200],"one":[3],"of":[4,51,130,136,178,187,196,206,221,227,235,241],"the":[5,40,49,66,75,93,98,102,137,175,179,184,188,197,219,222,228,233,236],"main":[6],"tasks":[7],"in":[8,61,70,128,154,157,204],"realizing":[9],"practical":[10],"intelligent":[11],"reflecting":[12],"surface-assisted":[13],"multi-user":[14],"communication":[15,22],"(IRS-MUC)":[16],"systems.":[17],"However,":[18],"different":[19],"from":[20,101],"traditional":[21],"systems,":[23,156],"an":[24,165,193],"IRS-MUC":[25,155],"system":[26],"generally":[27],"involves":[28],"a":[29,33,52,79,84,112,119,134,141,159],"cascaded":[30],"channel":[31,67,76,99,115,152,181],"with":[32,164],"sophisticated":[34],"statistical":[35],"distribution.":[36],"In":[37,191],"this":[38,71,107],"case,":[39],"optimal":[41,229],"minimum":[42],"mean":[43],"square":[44],"error":[45],"(MMSE)":[46],"estimator":[47,125,231],"requires":[48],"calculation":[50],"multidimensional":[53],"integration":[54],"which":[55,158],"intractable":[57],"to":[58,90,172,209],"be":[59],"implemented":[60],"practice.":[62],"To":[63,106],"further":[64],"improve":[65],"performance,":[69],"paper,":[72],"we":[73,109],"model":[74],"as":[78],"denoising":[80,161],"problem":[81],"and":[82,183,202],"adopt":[83],"deep":[85,120],"residual":[86,94,121],"learning":[87],"(DReL)":[88],"approach":[89],"implicitly":[91],"learn":[92],"noise":[95,189],"for":[96,151],"recovering":[97],"coefficients":[100],"noisy":[103,180],"pilot-based":[104],"observations.":[105],"end,":[108],"first":[110],"develop":[111],"versatile":[113],"DReL-based":[114],"framework":[117],"where":[118],"network":[122,144],"(DRN)-based":[123],"MMSE":[124,230],"derived":[127,201],"terms":[129,205],"Bayesian":[131,207],"philosophy.":[132],"As":[133],"realization":[135],"developed":[138],"DReL":[139],"framework,":[140],"convolutional":[142],"neural":[143],"(CNN)-based":[145],"DRN":[146],"(CDRN)":[147],"then":[149],"proposed":[150,198,223],"CNN":[160],"block":[162],"equipped":[163],"element-wise":[166],"subtraction":[167],"structure":[168],"specifically":[170],"designed":[171],"exploit":[173],"both":[174],"spatial":[176],"features":[177],"matrices":[182],"additive":[185],"nature":[186],"simultaneously.":[190],"particular,":[192],"explicit":[194],"expression":[195],"CDRN":[199],"analyzed":[203],"characterize":[210],"its":[211],"properties":[212],"theoretically.":[213],"Finally,":[214],"simulation":[215],"results":[216],"demonstrate":[217],"that":[218,226],"performance":[220],"method":[224],"approaches":[225],"requiring":[232],"availability":[234],"prior":[237],"probability":[238],"density":[239],"function":[240],"channel.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":44},{"year":2024,"cited_by_count":56},{"year":2023,"cited_by_count":54},{"year":2022,"cited_by_count":59},{"year":2021,"cited_by_count":8}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-09-08T00:00:00"}
