Yang Shunqi;Zeng Ying;Li Xiang;Li Yanfeng;Huang Hongzhong
{"title":"基于动态贝叶斯网络的无线通信网络可靠性分析","authors":"Yang Shunqi;Zeng Ying;Li Xiang;Li Yanfeng;Huang Hongzhong","doi":"10.23919/JSEE.2023.000130","DOIUrl":null,"url":null,"abstract":"The dynamic wireless communication network is a complex network that needs to consider various influence factors including communication devices, radio propagation, network topology, and dynamic behaviors. Existing works focus on suggesting simplified reliability analysis methods for these dynamic networks. As one of the most popular modeling methodologies, the dynamic Bayesian network (DBN) is proposed. However, it is insufficient for the wireless communication network which contains temporal and non-temporal events. To this end, we present a modeling methodology for a generalized continuous time Bayesian network (CTBN) with a 2-state conditional probability table (CPT). Moreover, a comprehensive reliability analysis method for communication devices and radio propagation is suggested. The proposed methodology is verified by a reliability analysis of a real wireless communication network.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 5","pages":"1368-1374"},"PeriodicalIF":1.9000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reliability analysis for wireless communication networks via dynamic Bayesian network\",\"authors\":\"Yang Shunqi;Zeng Ying;Li Xiang;Li Yanfeng;Huang Hongzhong\",\"doi\":\"10.23919/JSEE.2023.000130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The dynamic wireless communication network is a complex network that needs to consider various influence factors including communication devices, radio propagation, network topology, and dynamic behaviors. Existing works focus on suggesting simplified reliability analysis methods for these dynamic networks. As one of the most popular modeling methodologies, the dynamic Bayesian network (DBN) is proposed. However, it is insufficient for the wireless communication network which contains temporal and non-temporal events. To this end, we present a modeling methodology for a generalized continuous time Bayesian network (CTBN) with a 2-state conditional probability table (CPT). Moreover, a comprehensive reliability analysis method for communication devices and radio propagation is suggested. The proposed methodology is verified by a reliability analysis of a real wireless communication network.\",\"PeriodicalId\":50030,\"journal\":{\"name\":\"Journal of Systems Engineering and Electronics\",\"volume\":\"34 5\",\"pages\":\"1368-1374\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Systems Engineering and Electronics\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10308768/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Systems Engineering and Electronics","FirstCategoryId":"1087","ListUrlMain":"https://ieeexplore.ieee.org/document/10308768/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Reliability analysis for wireless communication networks via dynamic Bayesian network
The dynamic wireless communication network is a complex network that needs to consider various influence factors including communication devices, radio propagation, network topology, and dynamic behaviors. Existing works focus on suggesting simplified reliability analysis methods for these dynamic networks. As one of the most popular modeling methodologies, the dynamic Bayesian network (DBN) is proposed. However, it is insufficient for the wireless communication network which contains temporal and non-temporal events. To this end, we present a modeling methodology for a generalized continuous time Bayesian network (CTBN) with a 2-state conditional probability table (CPT). Moreover, a comprehensive reliability analysis method for communication devices and radio propagation is suggested. The proposed methodology is verified by a reliability analysis of a real wireless communication network.