{"id":"https://openalex.org/W3217304042","doi":"https://doi.org/10.3390/sym13112207","title":"Performance Estimation in V2X Networks Using Deep Learning-Based M-Estimator Loss Functions in the Presence of Outliers","display_name":"Performance Estimation in V2X Networks Using Deep Learning-Based M-Estimator Loss Functions in the Presence of Outliers","publication_year":2021,"publication_date":"2021-11-19","ids":{"openalex":"https://openalex.org/W3217304042","doi":"https://doi.org/10.3390/sym13112207","mag":"3217304042"},"language":"en","primary_location":{"id":"doi:10.3390/sym13112207","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13112207","pdf_url":"https://www.mdpi.com/2073-8994/13/11/2207/pdf?version=1637569613","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/13/11/2207/pdf?version=1637569613","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110818749","display_name":"Ali R. Abdellah","orcid":null},"institutions":[{"id":"https://openalex.org/I184834183","display_name":"Al-Azhar University","ror":"https://ror.org/05fnp1145","country_code":"EG","type":"education","lineage":["https://openalex.org/I184834183"]},{"id":"https://openalex.org/I37355250","display_name":"Saint-Petersburg State University of Telecommunications","ror":"https://ror.org/00pcyc255","country_code":"RU","type":"education","lineage":["https://openalex.org/I37355250"]}],"countries":["EG","RU"],"is_corresponding":true,"raw_author_name":"Ali R. Abdellah","raw_affiliation_strings":["Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 St. Petersburg, Russia","Electronics and Communications Engineering, Electrical Engineering Department, Faculty of Engineering, Al-Azhar University, Qena 83513, Egypt"],"raw_orcid":"https://orcid.org/0000-0001-8410-738X","affiliations":[{"raw_affiliation_string":"Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 St. Petersburg, Russia","institution_ids":["https://openalex.org/I37355250"]},{"raw_affiliation_string":"Electronics and Communications Engineering, Electrical Engineering Department, Faculty of Engineering, Al-Azhar University, Qena 83513, Egypt","institution_ids":["https://openalex.org/I184834183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102779093","display_name":"Abdullah Alshahrani","orcid":"https://orcid.org/0000-0002-5988-888X"},"institutions":[{"id":"https://openalex.org/I4210099699","display_name":"University of Jeddah","ror":"https://ror.org/015ya8798","country_code":"SA","type":"education","lineage":["https://openalex.org/I4210099699"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Abdullah Alshahrani","raw_affiliation_strings":["Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah 21493, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah 21493, Saudi Arabia","institution_ids":["https://openalex.org/I4210099699"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024357714","display_name":"Ammar Muthanna","orcid":"https://orcid.org/0000-0003-0213-8145"},"institutions":[{"id":"https://openalex.org/I126527374","display_name":"Peoples' Friendship University of Russia","ror":"https://ror.org/02dn9h927","country_code":"RU","type":"education","lineage":["https://openalex.org/I126527374"]},{"id":"https://openalex.org/I37355250","display_name":"Saint-Petersburg State University of Telecommunications","ror":"https://ror.org/00pcyc255","country_code":"RU","type":"education","lineage":["https://openalex.org/I37355250"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Ammar Muthanna","raw_affiliation_strings":["Applied Probability and Informatics, Peoples\u2019 Friendship University of Russia (RUDN University), 117198 Moscow, Russia","Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 St. Petersburg, Russia","Applied Probability and Informatics, Peoples' Friendship University of Russia (RUDN University), 117198 Moscow, Russia"],"raw_orcid":"https://orcid.org/0000-0003-0213-8145","affiliations":[{"raw_affiliation_string":"Applied Probability and Informatics, Peoples\u2019 Friendship University of Russia (RUDN University), 117198 Moscow, Russia","institution_ids":["https://openalex.org/I126527374"]},{"raw_affiliation_string":"Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 St. Petersburg, Russia","institution_ids":["https://openalex.org/I37355250"]},{"raw_affiliation_string":"Applied Probability and Informatics, Peoples' Friendship University of Russia (RUDN University), 117198 Moscow, Russia","institution_ids":["https://openalex.org/I126527374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018187110","display_name":"Andrey Koucheryavy","orcid":"https://orcid.org/0000-0003-4479-2479"},"institutions":[{"id":"https://openalex.org/I37355250","display_name":"Saint-Petersburg State University of Telecommunications","ror":"https://ror.org/00pcyc255","country_code":"RU","type":"education","lineage":["https://openalex.org/I37355250"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Andrey Koucheryavy","raw_affiliation_strings":["Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 St. Petersburg, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 St. Petersburg, Russia","institution_ids":["https://openalex.org/I37355250"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024357714","https://openalex.org/A5110818749"],"corresponding_institution_ids":["https://openalex.org/I126527374","https://openalex.org/I184834183","https://openalex.org/I37355250"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":0.6512,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.76381606,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"13","issue":"11","first_page":"2207","last_page":"2207"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9598000049591064,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.8504649996757507},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7801195383071899},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7800066471099854},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7490445375442505},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.5036408305168152},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4882338345050812},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48233410716056824},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.47980454564094543},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4444185495376587},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4148576557636261},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.39841604232788086},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1109144389629364},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09569427371025085},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08979290723800659}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8504649996757507},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7801195383071899},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7800066471099854},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7490445375442505},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.5036408305168152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4882338345050812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48233410716056824},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.47980454564094543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4444185495376587},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4148576557636261},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.39841604232788086},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1109144389629364},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09569427371025085},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08979290723800659},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym13112207","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13112207","pdf_url":"https://www.mdpi.com/2073-8994/13/11/2207/pdf?version=1637569613","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9bc9ce0d04d240379e3a076cabfa5ceb","is_oa":true,"landing_page_url":"https://doaj.org/article/9bc9ce0d04d240379e3a076cabfa5ceb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 13, Iss 11, p 2207 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/13/11/2207/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym13112207","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym13112207","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13112207","pdf_url":"https://www.mdpi.com/2073-8994/13/11/2207/pdf?version=1637569613","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3217304042.pdf"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2042678829","https://openalex.org/W2043698172","https://openalex.org/W2058009001","https://openalex.org/W2122053769","https://openalex.org/W2124331144","https://openalex.org/W2274279630","https://openalex.org/W2283079028","https://openalex.org/W2541498026","https://openalex.org/W2796104866","https://openalex.org/W2807834884","https://openalex.org/W2809684781","https://openalex.org/W2810563447","https://openalex.org/W2901008672","https://openalex.org/W2910166370","https://openalex.org/W2913786719","https://openalex.org/W2914940294","https://openalex.org/W2945906332","https://openalex.org/W2950863887","https://openalex.org/W2972717909","https://openalex.org/W2973449430","https://openalex.org/W2996165627","https://openalex.org/W2997616550","https://openalex.org/W3034578955","https://openalex.org/W3046936799","https://openalex.org/W3089831155","https://openalex.org/W3093257130","https://openalex.org/W3099769178","https://openalex.org/W3113913633","https://openalex.org/W3127355490","https://openalex.org/W3135028703","https://openalex.org/W3136945043","https://openalex.org/W3143519386","https://openalex.org/W3143583050","https://openalex.org/W3188101068","https://openalex.org/W4241773993","https://openalex.org/W4241946797","https://openalex.org/W4288948033","https://openalex.org/W4301959158","https://openalex.org/W6694491799","https://openalex.org/W6784018464"],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W4366700029","https://openalex.org/W3006513224","https://openalex.org/W4210897550","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Recently,":[0],"5G":[1,21],"networks":[2,16,22,97],"have":[3,176],"emerged":[4],"as":[5,99,179,183],"a":[6,46,56],"new":[7,48],"technology":[8],"that":[9],"can":[10],"control":[11],"the":[12,52,117,136,143,147,150,156,165,187,194,201,210],"advancement":[13],"of":[14,71,119,140,149,158,170,203,212],"telecommunication":[15],"and":[17,31,73,76,102,130,197],"transportation":[18],"systems.":[19],"Furthermore,":[20],"provide":[23],"better":[24],"network":[25,29,67,80,100],"performance":[26,114,157],"while":[27],"reducing":[28],"traffic":[30,81,161,216],"complexity":[32],"compared":[33],"to":[34,125,134,186,192],"current":[35],"networks.":[36],"Machine-learning":[37],"techniques":[38],"(ML)":[39],"will":[40],"help":[41],"symmetric":[42,72],"IoT":[43],"applications":[44],"become":[45],"significant":[47],"data":[49,145],"source":[50],"in":[51,60,65,79,94,142,200,209],"future.":[53],"Symmetry":[54],"is":[55,82,90,123],"widely":[57],"studied":[58],"pattern":[59],"various":[61],"research":[62],"areas,":[63],"especially":[64],"wireless":[66,96],"traffic.":[68],"The":[69,138],"study":[70],"asymmetric":[74],"faults":[75],"outliers":[77,141,213],"(anomalies)":[78],"an":[83,91,184],"important":[84],"topic.":[85],"Nowadays,":[86],"deep":[87],"learning":[88],"(DL)":[89],"advanced":[92],"approach":[93],"challenging":[95],"such":[98],"management":[101],"optimization,":[103],"anomaly":[104],"detection,":[105],"predictive":[106],"analysis,":[107],"lifetime":[108],"value":[109],"prediction,":[110],"etc.":[111],"However,":[112],"its":[113],"depends":[115],"on":[116,214],"efficiency":[118],"training":[120,151,195],"samples.":[121],"DL":[122,166,199],"designed":[124],"work":[126],"with":[127],"large":[128],"datasets":[129],"uses":[131],"complex":[132],"algorithms":[133],"train":[135],"model.":[137],"occurrence":[139],"raw":[144],"reduces":[146],"reliability":[148],"models.":[152],"In":[153],"this":[154],"paper,":[155],"Vehicle-to-Everything":[159],"(V2X)":[160],"was":[162],"estimated":[163],"using":[164],"algorithm.":[167],"A":[168],"set":[169],"robust":[171,180],"statistical":[172],"estimators,":[173],"called":[174],"M-estimators,":[175],"been":[177],"proposed":[178],"loss":[181,190],"functions":[182],"alternative":[185],"traditional":[188],"MSE":[189],"function,":[191],"improve":[193],"process":[196],"robustize":[198],"presence":[202,211],"outliers.":[204],"We":[205],"demonstrate":[206],"their":[207],"robustness":[208],"V2X":[215],"datasets.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
