{"title":"A test of homogeneity for RSS measurements within a wireless sensor network","authors":"F. Bandiera, A. Coluccia, G. Ricci","doi":"10.1109/INISTA.2014.6873594","DOIUrl":null,"url":null,"abstract":"In this paper, we use the tools of statistical hypothesis testing to determine whether or not the different links of a WSN are homogeneous. At the design stage we use a statistical path loss law to model the RSS measurements. More precisely, in the homogeneous case all links share one and the same attenuation factor while in the non-homogeneous one the attenuation factors of the various links are different. We thus derive a GLRT-based decision rule for the considered problem and compute its distribution. Some numerical examples are finally presented to evaluate the potential to discriminate between the two hypotheses.","PeriodicalId":339652,"journal":{"name":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INISTA.2014.6873594","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
In this paper, we use the tools of statistical hypothesis testing to determine whether or not the different links of a WSN are homogeneous. At the design stage we use a statistical path loss law to model the RSS measurements. More precisely, in the homogeneous case all links share one and the same attenuation factor while in the non-homogeneous one the attenuation factors of the various links are different. We thus derive a GLRT-based decision rule for the considered problem and compute its distribution. Some numerical examples are finally presented to evaluate the potential to discriminate between the two hypotheses.