{"id":"https://openalex.org/W4414538987","doi":"https://doi.org/10.1109/icc52391.2025.11161625","title":"Meta-Learning-Based Channel Denoising for MIMO-OFDM Systems","display_name":"Meta-Learning-Based Channel Denoising for MIMO-OFDM Systems","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414538987","doi":"https://doi.org/10.1109/icc52391.2025.11161625"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161625","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5034621834","display_name":"Sohmyung Ha","orcid":"https://orcid.org/0000-0003-3589-086X"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungyoung Ha","raw_affiliation_strings":["POSTECH,Department of Electrical Engineering,Pohang,Gyeongbuk,South Korea,37673"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"POSTECH,Department of Electrical Engineering,Pohang,Gyeongbuk,South Korea,37673","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074188581","display_name":"Ikbeom Lee","orcid":"https://orcid.org/0000-0002-9131-8107"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ikbeom Lee","raw_affiliation_strings":["Samsung Electronics Co., Ltd.,Samsung Research,Seoul,South Korea,06765"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics Co., Ltd.,Samsung Research,Seoul,South Korea,06765","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012803748","display_name":"Yo\u2013Seb Jeon","orcid":"https://orcid.org/0000-0002-2886-157X"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yo-Seb Jeon","raw_affiliation_strings":["POSTECH,Department of Electrical Engineering,Pohang,Gyeongbuk,South Korea,37673"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"POSTECH,Department of Electrical Engineering,Pohang,Gyeongbuk,South Korea,37673","institution_ids":["https://openalex.org/I123900574"]}]}],"institutions":[],"countries_distinct_count":1,"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":"4768","last_page":"4773"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9909999966621399,"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":0.9909999966621399,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9861000180244446,"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"}},{"id":"https://openalex.org/T13905","display_name":"Telecommunications and Broadcasting Technologies","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/channel","display_name":"Channel (broadcasting)","score":0.7491000294685364},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6071000099182129},{"id":"https://openalex.org/keywords/orthogonal-frequency-division-multiplexing","display_name":"Orthogonal frequency-division multiplexing","score":0.48019999265670776},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.429500013589859},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4117000102996826},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4020000100135803},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3684999942779541}],"concepts":[{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.7491000294685364},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6366999745368958},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6071000099182129},{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.48019999265670776},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.429500013589859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42340001463890076},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4117000102996826},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4020000100135803},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37720000743865967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.36559998989105225},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C89061704","wikidata":"https://www.wikidata.org/wiki/Q5555726","display_name":"Frequency-division multiplexing","level":4,"score":0.27709999680519104},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11161625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161625","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/W2092235212","https://openalex.org/W2123331874","https://openalex.org/W2136180922","https://openalex.org/W2155308272","https://openalex.org/W2162888803","https://openalex.org/W2164528346","https://openalex.org/W2508457857","https://openalex.org/W2963836746","https://openalex.org/W3110675837","https://openalex.org/W3163842339","https://openalex.org/W4225460810","https://openalex.org/W4311009203","https://openalex.org/W4368232630"],"related_works":[],"abstract_inverted_index":{"Multiple-input":[0],"multiple-output":[1],"orthogonal":[2],"frequency":[3,30,63],"division":[4],"multiplexing":[5],"(MIMO-OFDM)":[6],"systems":[7],"often":[8],"suffer":[9],"from":[10,101,122],"channel":[11,23,41,62,92,156,164,170,183],"estimation":[12,59,171],"errors":[13,60,172],"due":[14],"to":[15,57,88,108,127,179],"the":[16,27,67,72,86,110,113,129,162,169],"limited":[17],"number":[18],"of":[19,85,173],"reference":[20],"signals":[21],"and":[22,29,90,176,181],"selectivity":[24],"in":[25,61],"both":[26],"time":[28],"domains.":[31],"To":[32],"address":[33],"these":[34],"errors,":[35],"this":[36],"paper":[37],"proposes":[38],"a":[39,51,74,118,134],"meta-learning-based":[40],"denoising":[42,52,93,165],"method":[43,49,166],"for":[44],"MIMO-OFDM":[45],"systems.":[46],"The":[47],"proposed":[48,163],"employs":[50],"convolutional":[53],"neural":[54],"network":[55],"(DnCNN)":[56],"mitigate":[58],"responses":[64],"(CFRs)":[65],"across":[66],"time-frequency":[68],"domain.":[69],"For":[70],"training":[71,99,120],"DnCNN,":[73,111],"model-agnostic":[75],"meta-learning":[76],"(MAML)":[77],"approach":[78],"is":[79,143],"devised":[80],"which":[81],"enables":[82],"fast":[83],"adaptation":[84],"DnCNN":[87,131],"new":[89,123,180],"unseen":[91,182],"tasks.":[94],"In":[95],"our":[96],"MAML":[97,114],"approach,":[98],"samples":[100,121],"past":[102],"user":[103],"equipments":[104],"(UEs)":[105],"are":[106,125],"used":[107],"pre-train":[109],"following":[112],"principle.":[115],"After":[116],"pre-training,":[117],"few":[119,135],"UEs":[124],"utilized":[126],"fine-tune":[128],"pre-trained":[130],"using":[132],"only":[133],"gradient":[136],"steps.":[137],"A":[138],"practical":[139],"data":[140],"generation":[141],"strategy":[142],"also":[144],"presented,":[145],"substituting":[146],"true":[147],"CFRs":[148],"with":[149],"high-quality":[150],"CFR":[151],"estimates":[152],"determined":[153],"via":[154],"data-aided":[155],"estimation.":[157],"Simulation":[158],"results":[159],"show":[160],"that":[161],"effectively":[167],"reduces":[168],"conventional":[174],"techniques":[175],"adapts":[177],"well":[178],"environments.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
