Statistical Analysis of Wireless Communication Systems Using Hidden Markov Models

dc.contributor.authorRouf, Ishtiaqen
dc.contributor.committeechairTranter, William H.en
dc.contributor.committeememberPratt, Timothy J.en
dc.contributor.committeememberReed, Jeffrey H.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.description.abstractThis thesis analyzes the use of hidden Markov models (HMM) in wireless communication systems. HMMs are a probabilistic method which is useful for discrete channel modeling. The simulations done in the thesis verified a previously formulated methodology. Power delay profiles (PDP) of twelve wireless receivers were used for the experiment. To reduce the computational burden, binary HMMs were used. The PDP measurements were sampled to identify static receivers and grid-based analysis. This work is significant as it has been performed in a new environment. Stochastic game theory is analyzed to gain insight into the decision-making process of HMMs. Study of game theory is significant because it analyzes rational decisions in detail by attaching risk and reward to every possibility. Network security situation awareness has emerged as a novel application of HMMs in wireless networking. The dually stochastic nature of HMMs is applied in this process for behavioral analysis of network intrusion. The similarity of HMMs to artificial neural networks makes it useful for such applications. This application was performed using simulations similar to the original works.en
dc.description.degreeMaster of Scienceen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.subjectStochastic Gamesen
dc.subjectPosition Locationen
dc.subjectHidden Markov Modelen
dc.subjectNetwork Security Situation Awarenessen
dc.titleStatistical Analysis of Wireless Communication Systems Using Hidden Markov Modelsen
dc.typeThesisen and Computer Engineeringen Polytechnic Institute and State Universityen of Scienceen


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