Time series forecasting for rural fixed-wireless communication network monitoring

dc.contributor.advisorPetersen, Brent R.
dc.contributor.authorColpitts, Alexander Gordon Bruce
dc.date.accessioned2024-04-22T18:16:55Z
dc.date.available2024-04-22T18:16:55Z
dc.date.issued2023-12
dc.description.abstractLTE and 5G cellular networks are evolving at a rapid pace to accommodate more users and higher traffic. Existing studies have largely focused on urban mobile networks, leaving their rural fixed-wireless counterparts largely ignored. This work investigates the performance of a rural Canadian fixed wireless network on several time scales. Short- and long-term performance properties are considered. It is well known that rural propagation environments behave differently from urban ones. Long-term temporal changes in the propagation environment, such as foliage and snow, were shown to have a small impact on the performance of the network. From a forecasting point of view, it was shown that including environmental features and increasing the time horizon of the forecasts will increase the accuracy of the forecast. In contrast, it was shown that including environmental features did not provide any benefit to short-term forecast accuracy; however, longer input sequence lengths were demonstrated to be beneficial for short-term forecasts. Finally, an unsupervised anomaly detection algorithm, RAINFOREST, is presented which leverages the temporal context obtained from the forecasts alongside density-based clustering analysis to outperform all the baselines tested.
dc.description.copyright© Alexander Gordon Bruce Colpitts, 2023
dc.format.extentxviii, 199
dc.format.mediumelectronic
dc.identifier.oclc(OCoLC)1440189695en
dc.identifier.otherThesis 11343en
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/37786
dc.language.isoen
dc.publisherUniversity of New Brunswick
dc.relationMITACS
dc.relationNBIF
dc.relationUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineElectrical and Computer Engineering
dc.subject.lcshAlgorithms.en
dc.subject.lcshRural development--Canada.en
dc.subject.lcshWireless communication systems--Canada--Forecasting.en
dc.subject.lcshCanada.en
dc.titleTime series forecasting for rural fixed-wireless communication network monitoring
dc.typedoctoral thesis
oaire.license.conditionother
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.leveldoctorate
thesis.degree.namePh.D.

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