{"id":"https://openalex.org/W3200875445","doi":"https://doi.org/10.1109/tvt.2021.3111081","title":"Channel Estimation and User Identification With Deep Learning for Massive Machine-Type Communications","display_name":"Channel Estimation and User Identification With Deep Learning for Massive Machine-Type Communications","publication_year":2021,"publication_date":"2021-09-13","ids":{"openalex":"https://openalex.org/W3200875445","doi":"https://doi.org/10.1109/tvt.2021.3111081","mag":"3200875445"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2021.3111081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2021.3111081","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"},"type":"article","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/A5049642519","display_name":"Bryan Liu","orcid":"https://orcid.org/0000-0001-7153-8885"},"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":true,"raw_author_name":"Bryan Liu","raw_affiliation_strings":["School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074077175","display_name":"Zhiqiang Wei","orcid":"https://orcid.org/0000-0003-3400-5590"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Zhiqiang Wei","raw_affiliation_strings":["Institute for Digital Communications (IDC), Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Digital Communications (IDC), Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011236120","display_name":"Weijie Yuan","orcid":"https://orcid.org/0000-0002-2158-0046"},"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":"Weijie Yuan","raw_affiliation_strings":["School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091837980","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, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042113276","display_name":"Milutin Pajovic","orcid":"https://orcid.org/0000-0001-5033-017X"},"institutions":[{"id":"https://openalex.org/I117023288","display_name":"Analog Devices (United States)","ror":"https://ror.org/01545pm61","country_code":"US","type":"company","lineage":["https://openalex.org/I117023288"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Milutin Pajovic","raw_affiliation_strings":["Analog Garage, ADI, Boston, Massachusetts, USA"],"affiliations":[{"raw_affiliation_string":"Analog Garage, ADI, Boston, Massachusetts, USA","institution_ids":["https://openalex.org/I117023288"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5049642519"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.9797,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.80839453,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"70","issue":"10","first_page":"10709","last_page":"10722"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T10964","display_name":"Wireless Communication Security Techniques","score":0.9991000294685364,"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":0.9988999962806702,"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/computer-science","display_name":"Computer science","score":0.6900962591171265},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6089465618133545},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.5387457609176636},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5350369811058044},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.48977088928222656},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.46402862668037415},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4386715292930603},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40818920731544495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4037955403327942},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14023756980895996},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13176584243774414},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07934123277664185}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6900962591171265},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6089465618133545},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.5387457609176636},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5350369811058044},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.48977088928222656},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.46402862668037415},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4386715292930603},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40818920731544495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4037955403327942},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14023756980895996},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13176584243774414},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07934123277664185},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2021.3111081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2021.3111081","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2361132057","display_name":null,"funder_award_id":"DP190101363","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1525535255","https://openalex.org/W1533861849","https://openalex.org/W1539800233","https://openalex.org/W1577058430","https://openalex.org/W1906261441","https://openalex.org/W1941452196","https://openalex.org/W2026933032","https://openalex.org/W2072184935","https://openalex.org/W2082029531","https://openalex.org/W2118103795","https://openalex.org/W2131774270","https://openalex.org/W2157331557","https://openalex.org/W2203038008","https://openalex.org/W2220485312","https://openalex.org/W2603333836","https://openalex.org/W2619204584","https://openalex.org/W2625429595","https://openalex.org/W2666368276","https://openalex.org/W2767434619","https://openalex.org/W2778904866","https://openalex.org/W2784331297","https://openalex.org/W2786361328","https://openalex.org/W2890736047","https://openalex.org/W2900584518","https://openalex.org/W2913780741","https://openalex.org/W2937714515","https://openalex.org/W2945463326","https://openalex.org/W2947762896","https://openalex.org/W2951236102","https://openalex.org/W2962743139","https://openalex.org/W2962886963","https://openalex.org/W2963290405","https://openalex.org/W2963641440","https://openalex.org/W2970195506","https://openalex.org/W2980526710","https://openalex.org/W2985210419","https://openalex.org/W2998650708","https://openalex.org/W3006563626","https://openalex.org/W3006643426","https://openalex.org/W3008148299","https://openalex.org/W3008218996","https://openalex.org/W3009376554","https://openalex.org/W3100774664","https://openalex.org/W3120440980","https://openalex.org/W4206180546","https://openalex.org/W4248709896","https://openalex.org/W4294529512","https://openalex.org/W6634623672","https://openalex.org/W6677645113","https://openalex.org/W6687909239","https://openalex.org/W6739495466","https://openalex.org/W6745995898","https://openalex.org/W6772615008"],"related_works":["https://openalex.org/W2067317451","https://openalex.org/W4211085505","https://openalex.org/W2154771632","https://openalex.org/W2084758217","https://openalex.org/W3122478268","https://openalex.org/W2102148524","https://openalex.org/W408804804","https://openalex.org/W3086365953","https://openalex.org/W4226072953","https://openalex.org/W2392606101"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,74,136],"investigate":[4],"the":[5,29,42,57,69,86,92,97,102,121,129,146,153,167,181,186,192],"detection":[6,155],"problem":[7],"for":[8],"a":[9,76,111,116,138,158,172],"massive":[10],"machine-type":[11],"communication":[12],"(mMTC)":[13],"system":[14],"that":[15,142,166],"has":[16],"correlated":[17],"user":[18,30,38,45,87,93,123,132,147,193],"activities.":[19],"Two":[20],"deep":[21,77],"learning":[22,78],"assisted":[23],"algorithms":[24],"are":[25],"proposed":[26,168],"to":[27,33,41,145,180],"exploit":[28],"activity":[31,88,94,133],"correlation":[32,95],"facilitate":[34],"channel":[35],"estimation":[36],"and":[37,185],"identification.":[39],"Due":[40],"dependency":[43],"among":[44],"activities,":[46],"conventional":[47,122,182],"element-wise":[48],"minimum":[49],"mean":[50,174],"square":[51],"error":[52,176],"(MMSE)":[53],"denoiser":[54,99],"used":[55],"in":[56,96,120,128],"orthogonal":[58],"approximate":[59],"message":[60],"passing":[61],"(OAMP)":[62],"algorithm":[63,170,184,188],"cannot":[64],"achieve":[65],"satisfying":[66],"performance":[67,177],"during":[68,105],"two-step":[70],"iterative":[71],"process.":[72],"Therefore,":[73],"propose":[75,137],"modified":[79],"OAMP":[80,107,183],"(DL-mOAMP)":[81],"algorithm,":[82],"which":[83,151],"iteratively":[84],"modifies":[85],"ratio":[89],"via":[90],"exploiting":[91],"MMSE":[98],"based":[100],"on":[101],"estimated":[103],"sequence":[104],"each":[106],"iteration.":[108],"Moreover,":[109],"given":[110],"specific":[112],"false":[113,160],"alarm":[114,161],"probability,":[115],"constant":[117],"threshold":[118],"employed":[119],"identification":[124,148,194],"is":[125,143],"not":[126],"optimal":[127],"presence":[130],"of":[131,196],"correlation.":[134],"Thus,":[135],"neural":[139],"network":[140],"framework":[141],"dedicated":[144],"(DL-mOAMP-UI":[149],"algorithm),":[150],"minimizes":[152],"missed":[154],"probability":[156],"under":[157],"pre-determined":[159],"probability.":[162],"Numerical":[163],"results":[164],"show":[165],"DL-mOAMP":[169],"provides":[171],"substantial":[173],"squared":[175],"gain":[178],"compared":[179],"DL-mOAMP-UI":[187],"can":[189],"further":[190],"improve":[191],"accuracy":[195],"an":[197],"mMTC":[198],"system.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
