{"title":"Blind estimation of wireless network topology and throughput","authors":"Daniel Salmond","doi":"10.1109/CISS.2019.8692903","DOIUrl":null,"url":null,"abstract":"Wireless communications networks can be modelled as cascades of emission events, which makes them amenable to being modelled as multivariate Hawkes processes (MHPs). The MHP parameters can then be used to evaluate an attributability matrix, which describes the probability that each emission event can be attributed to previous events. Methods for inferring probabilistic adjacency matrices and network throughput estimates from these attributability matrices are demonstrated.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISS.2019.8692903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Wireless communications networks can be modelled as cascades of emission events, which makes them amenable to being modelled as multivariate Hawkes processes (MHPs). The MHP parameters can then be used to evaluate an attributability matrix, which describes the probability that each emission event can be attributed to previous events. Methods for inferring probabilistic adjacency matrices and network throughput estimates from these attributability matrices are demonstrated.
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