{"id":"https://openalex.org/W7224824080","doi":"https://doi.org/10.1109/icsip70099.2026.11744241","title":"MUC2I: A Low-Redundancy CSI Preprocessing Method for Multi-User Wireless Human Activity Recognition","display_name":"MUC2I: A Low-Redundancy CSI Preprocessing Method for Multi-User Wireless Human Activity Recognition","publication_year":2026,"publication_date":"2026-07-01","ids":{"openalex":"https://openalex.org/W7224824080","doi":"https://doi.org/10.1109/icsip70099.2026.11744241"},"language":"en","primary_location":{"id":"doi:10.1109/icsip70099.2026.11744241","doi":"https://doi.org/10.1109/icsip70099.2026.11744241","is_oa":true,"landing_page_url":"https://doi.org/10.1109/icsip70099.2026.11744241","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 11th International Conference on Signal and Image Processing (ICSIP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/icsip70099.2026.11744241","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113512194","display_name":"Yangjing Zhou","orcid":"https://orcid.org/0000-0003-4112-7393","observed_orcids":["https://orcid.org/0000-0003-4112-7393"]},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Yangjing Zhou","raw_affiliation_strings":["Macao Polytechnic University"],"raw_orcid":"https://orcid.org/0000-0003-4112-7393","affiliations":[{"raw_affiliation_string":"Macao Polytechnic University","institution_ids":["https://openalex.org/I49835588"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320066","display_name":"Yue Liu","orcid":"https://orcid.org/0000-0002-3292-4211","observed_orcids":["https://orcid.org/0000-0002-3292-4211","https://orcid.org/0009-0008-9379-3172"]},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Yue Liu","raw_affiliation_strings":["Macao Polytechnic University"],"raw_orcid":"https://orcid.org/0000-0002-3292-4211","affiliations":[{"raw_affiliation_string":"Macao Polytechnic University","institution_ids":["https://openalex.org/I49835588"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112542804","display_name":"Chuan Liu","orcid":"https://orcid.org/0009-0009-4431-067X","observed_orcids":["https://orcid.org/0009-0009-4431-067X"]},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Chuan Liu","raw_affiliation_strings":["Macao Polytechnic University"],"raw_orcid":"https://orcid.org/0009-0009-4431-067X","affiliations":[{"raw_affiliation_string":"Macao Polytechnic University","institution_ids":["https://openalex.org/I49835588"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I49835588"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"806","last_page":"810"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.44290000200271606,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.44290000200271606,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.4059999883174896,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.015599999576807022,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/integrated-sensing-and-communication","display_name":"integrated sensing and communication","score":0.8370000123977661},{"id":"https://openalex.org/keywords/scale-normalization","display_name":"scale normalization","score":0.7160000205039978},{"id":"https://openalex.org/keywords/bicubic-interpolation","display_name":"bicubic interpolation","score":0.9919999837875366},{"id":"https://openalex.org/keywords/edge-cloud-deployment","display_name":"edge-cloud deployment","score":0.7279999852180481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.663100004196167},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.5831000208854675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5770000219345093},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4250999987125397},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4083000123500824},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.328900009393692},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsip70099.2026.11744241","doi":"https://doi.org/10.1109/icsip70099.2026.11744241","is_oa":true,"landing_page_url":"https://doi.org/10.1109/icsip70099.2026.11744241","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 11th International Conference on Signal and Image Processing (ICSIP)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/icsip70099.2026.11744241","doi":"https://doi.org/10.1109/icsip70099.2026.11744241","is_oa":true,"landing_page_url":"https://doi.org/10.1109/icsip70099.2026.11744241","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 11th International Conference on Signal and Image Processing (ICSIP)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2157494358","https://openalex.org/W2168821867","https://openalex.org/W2820000974","https://openalex.org/W2899145720","https://openalex.org/W2938514801","https://openalex.org/W2940661151","https://openalex.org/W2950821050","https://openalex.org/W2981892815","https://openalex.org/W3176590546","https://openalex.org/W3177106557","https://openalex.org/W3207267999","https://openalex.org/W4211045302","https://openalex.org/W4226424792","https://openalex.org/W4306174033","https://openalex.org/W4322627157","https://openalex.org/W4387415161","https://openalex.org/W4390481160","https://openalex.org/W4391742790","https://openalex.org/W4399727947","https://openalex.org/W4401990498","https://openalex.org/W4403021224","https://openalex.org/W4403447973","https://openalex.org/W4405178969","https://openalex.org/W4407900434","https://openalex.org/W4410295608","https://openalex.org/W4415624296","https://openalex.org/W7118404468","https://openalex.org/W7124470822"],"related_works":["https://openalex.org/W7018372722","https://openalex.org/W7223027967","https://openalex.org/W7224562173","https://openalex.org/W7124904049","https://openalex.org/W7165785049","https://openalex.org/W7169859724","https://openalex.org/W7201833146","https://openalex.org/W7015752277","https://openalex.org/W7167499934","https://openalex.org/W7167622918"],"abstract_inverted_index":{"Wireless":[0],"Multi-User":[1],"Human":[2],"Activity":[3],"Recognition":[4],"(WMUHAR)":[5],"enables":[6],"non-invasive,":[7],"device-free":[8],"motion":[9],"monitoring.":[10],"As":[11],"a":[12,71,130],"key":[13],"Integrated":[14],"Sensing":[15],"and":[16,22,49,64,96,157,172],"Communication":[17],"application":[18],"in":[19,28,138,153],"smart":[20],"homes":[21],"healthcare,":[23],"it":[24],"faces":[25],"deployment":[26],"challenges":[27],"edge-cloud":[29],"environments":[30],"due":[31],"to":[32,60,90,93],"the":[33,101,121,139],"high":[34,82],"dimensionality":[35],"of":[36,55],"Channel":[37],"State":[38],"Information":[39],"(CSI)":[40],"data.":[41],"Existing":[42],"deep-learning":[43],"WMUHAR":[44],"research":[45],"prioritizes":[46],"accuracy":[47,133,156],"optimization":[48],"model":[50],"lightweighting":[51],"but":[52],"overlooks":[53],"compression":[54,159],"raw":[56,91],"CSI":[57,73,92,145],"signals,":[58],"leading":[59],"excessive":[61],"communication,":[62],"storage,":[63],"computational":[65],"costs.":[66],"This":[67],"paper":[68],"introduces":[69],"MUC2I,":[70],"low-redundancy":[72],"preprocessing":[74],"method":[75],"that":[76,125],"reduces":[77],"data":[78,103,158],"volume":[79],"while":[80,142],"maintaining":[81],"recognition":[83,155],"accuracy.":[84],"MUC2I":[85,128],"first":[86],"applies":[87],"scale":[88],"normalization":[89],"mitigate":[94],"hardware":[95],"environmental":[97],"interference,":[98],"then":[99],"converts":[100],"normalized":[102],"into":[104],"pseudo":[105],"three-channel":[106],"images":[107],"for":[108,115,160],"efficient":[109],"representation,":[110],"enhanced":[111],"by":[112,148,167],"bicubic":[113],"interpolation":[114],"richer":[116],"perceptual":[117],"details.":[118],"Experiments":[119],"on":[120],"WiMANS":[122],"dataset":[123],"demonstrate":[124],"WiGRUNT":[126],"with":[127],"achieves":[129],"9%":[131],"average":[132],"improvement":[134],"over":[135],"existing":[136],"methods":[137],"5GHz":[140],"band,":[141],"reducing":[143],"preprocessed":[144],"file":[146],"size":[147],"83.3%,":[149],"showing":[150],"excellent":[151],"performance":[152],"both":[154],"complex":[161],"multiuser":[162],"scenarios.11This":[163],"work":[164],"is":[165,177],"supported":[166],"Macao":[168],"Polytechnic":[169],"University":[170],"(RP/FCA-03/2026":[171],"No.fca.66f4.9e39.a).":[173],"The":[174],"corresponding":[175],"author":[176],"Yue":[178],"Liu.":[179]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-10-31T00:00:00"}