{"title":"无线通信网络的量子可靠性分析","authors":"E. Zio","doi":"10.1177/1748006x231182455","DOIUrl":null,"url":null,"abstract":"This work is positioned within the new field of quantum probability theory and its application to the reliability analysis of wireless telecommunication networks. Specifically, we present the development of a Quantum Bayesian Network (QBN) for calculating the reliability of a 5G wireless telecommunication network. The qualitative comparison with a classical Bayesian Network model allows highlighting the role of interferences in the calculation of the reliability of a complex system such as a wireless telecommunication network.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantum reliability analysis of a wireless telecommunication network\",\"authors\":\"E. Zio\",\"doi\":\"10.1177/1748006x231182455\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work is positioned within the new field of quantum probability theory and its application to the reliability analysis of wireless telecommunication networks. Specifically, we present the development of a Quantum Bayesian Network (QBN) for calculating the reliability of a 5G wireless telecommunication network. The qualitative comparison with a classical Bayesian Network model allows highlighting the role of interferences in the calculation of the reliability of a complex system such as a wireless telecommunication network.\",\"PeriodicalId\":51266,\"journal\":{\"name\":\"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1177/1748006x231182455\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/1748006x231182455","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Quantum reliability analysis of a wireless telecommunication network
This work is positioned within the new field of quantum probability theory and its application to the reliability analysis of wireless telecommunication networks. Specifically, we present the development of a Quantum Bayesian Network (QBN) for calculating the reliability of a 5G wireless telecommunication network. The qualitative comparison with a classical Bayesian Network model allows highlighting the role of interferences in the calculation of the reliability of a complex system such as a wireless telecommunication network.
期刊介绍：
The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome
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