{"id":"https://openalex.org/W4392158244","doi":"https://doi.org/10.1109/globecom54140.2023.10437335","title":"Intelligent Reflecting Surface Aided Activity Detection: A Covariance-Based Learning Approach","display_name":"Intelligent Reflecting Surface Aided Activity Detection: A Covariance-Based Learning Approach","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4392158244","doi":"https://doi.org/10.1109/globecom54140.2023.10437335"},"language":"en","primary_location":{"id":"doi:10.1109/globecom54140.2023.10437335","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/globecom54140.2023.10437335","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","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/A5090195902","display_name":"Qingfeng Lin","orcid":"https://orcid.org/0000-0003-0181-7437"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Qingfeng Lin","raw_affiliation_strings":["The University of Hong Kong,Department of Electrical and Electronic Engineering,Hong Kong","Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong","Shenzhen Research Institute of Big Data, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Electrical and Electronic Engineering,Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Shenzhen Research Institute of Big Data, Shenzhen, China","institution_ids":["https://openalex.org/I4210099586"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319866","display_name":"Li Yang","orcid":"https://orcid.org/0000-0002-9337-1382"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["Shenzhen Research Institute of Big Data,Shenzhen,China","Pazhou Laboratory (Huangpu), Guangzhou, China","Peng Cheng Laboratory, Shenzhen, China","Shenzhen Research Institute of Big Data, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data,Shenzhen,China","institution_ids":["https://openalex.org/I4210099586"]},{"raw_affiliation_string":"Pazhou Laboratory (Huangpu), Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"Shenzhen Research Institute of Big Data, Shenzhen, China","institution_ids":["https://openalex.org/I4210099586"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085964667","display_name":"Yik\u2010Chung Wu","orcid":"https://orcid.org/0000-0002-2738-0387"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yik-Chung Wu","raw_affiliation_strings":["The University of Hong Kong,Department of Electrical and Electronic Engineering,Hong Kong","Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Electrical and Electronic Engineering,Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100422102","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0002-8729-8393"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]},{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN","SG"],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["Shenzhen Research Institute of Big Data,Shenzhen,China","Department of Electrical and Computer Engineering, National University of Singapore, Singapore","School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China","Shenzhen Research Institute of Big Data, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data,Shenzhen,China","institution_ids":["https://openalex.org/I4210099586"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"Shenzhen Research Institute of Big Data, Shenzhen, China","institution_ids":["https://openalex.org/I4210099586"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"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":"4853","last_page":"4858"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9907000064849854,"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":0.9907000064849854,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9811999797821045,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.630562961101532},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5928643345832825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5038785338401794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35265254974365234},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.138616144657135},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10633835196495056}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.630562961101532},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5928643345832825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5038785338401794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35265254974365234},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.138616144657135},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10633835196495056}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom54140.2023.10437335","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/globecom54140.2023.10437335","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W250076511","https://openalex.org/W1978026911","https://openalex.org/W2706056020","https://openalex.org/W2811365745","https://openalex.org/W2890736047","https://openalex.org/W2920228847","https://openalex.org/W2961179947","https://openalex.org/W2963116117","https://openalex.org/W3010632924","https://openalex.org/W3096252532","https://openalex.org/W3109886790","https://openalex.org/W3129486236","https://openalex.org/W3188366979","https://openalex.org/W3202416460","https://openalex.org/W4282978725","https://openalex.org/W4295789396","https://openalex.org/W4312922447","https://openalex.org/W4317794525"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"a":[3,106,122],"covariance-based":[4,27,40,120,141,150],"learning":[5,123,151],"approach":[6,28,41,124],"for":[7,100],"intelligent":[8],"reflecting":[9],"surface":[10],"(IRS)":[11],"aided":[12],"activity":[13,142],"detection":[14],"in":[15,109],"massive":[16],"machine-type":[17],"communications":[18],"(mMTC).":[19],"In":[20],"the":[21,26,34,39,45,51,55,62,65,71,82,86,90,101,110,114,119,131,137,140,145,148],"conventional":[22],"scenario":[23],"without":[24],"IRS,":[25],"has":[29],"been":[30],"demonstrated":[31],"to":[32,70,80,128],"outperform":[33],"compressed":[35],"sensing":[36],"approach,":[37],"as":[38],"can":[42],"well":[43],"exploit":[44],"probability":[46],"density":[47],"function":[48],"(PDF)":[49],"of":[50,64,85,113,139,147],"received":[52,87,115],"signals":[53,88],"at":[54,89],"base":[56],"station":[57],"(BS).":[58],"However,":[59],"when":[60],"taking":[61],"impact":[63],"IRS":[66],"into":[67],"account,":[68],"due":[69],"newly":[72],"introduced":[73],"cascaded":[74],"channels,":[75],"it":[76],"is":[77,125],"quite":[78],"difficult":[79],"obtain":[81],"exact":[83],"PDF":[84,103],"BS.":[91],"To":[92],"tackle":[93],"this":[94],"challenge,":[95],"we":[96],"propose":[97],"an":[98],"approximation":[99],"intended":[102],"by":[104],"modeling":[105],"correlation":[107,132],"parameter":[108],"covariance":[111],"matrix":[112],"signals.":[116],"Based":[117],"on":[118],"formulation,":[121],"further":[126],"proposed":[127,149],"automatically":[129],"learn":[130],"parameter.":[133],"Simulation":[134],"results":[135],"demonstrate":[136],"performance":[138],"detection,":[143],"and":[144],"superiority":[146],"approach.":[152]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}