A master thesis from Aalborg University
'Stochastic Channel Modelling: A Bayesian approach using reversible jump Markov chain Monte Carlo methods'
Author(s)
Term
4. term
Education
Publication year
2006
Submitted on
2012-02-14
Abstract
'This thesis presents a number of stochastic models and statistical methods for stochastic channel modeling. The purpose of this is to describe the statistical modeling and estimation of an impulse response function for an ultra wide band radio channel, in a rigorous mathematical context. Previous stochastic models are presented and reformulated using the theory of point processes. The thesis provides brief descriptions of basic likelihood and Bayesian inference. The likelihood section introduces the expectation maximization algorithm, and an approach on how to implement this for inference in the statistical modeling of an impulse response function. The theory of Markov chain Monte Carlo methods and the reversible jump Markov chain Monte Carlo algorithm is presented, for estimation purposes. In the second part of the thesis an algorithm, based on the theory from the first part, is constructed, with the purpose of performing statistical inference on measurements of an impulse response function. The purpose is to fit a parametric model of an impulse response function to measured data.'
Documents
Colophon: This page is part of the AAU Student Projects portal, which is run by Aalborg University. Here, you can find and download publicly available bachelor's theses and master's projects from across the university dating from 2008 onwards. Student projects from before 2008 are available in printed form at Aalborg University Library.
If you have any questions about AAU Student Projects or the research registration, dissemination and analysis at Aalborg University, please feel free to contact the VBN team. You can also find more information in the AAU Student Projects FAQs.