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A mathematical framework for expressing multivariate distributions useful in wireless communications
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- Author / Creator
- Hemachandra, Kasun Thilina
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Multivariate statistics play an important role in performance analysis of wireless communication
systems in correlated fading channels. This thesis presents a framework which can
be used to derive easily computable mathematical representations for some multivariate statistical
distributions, which are derivatives of the Gaussian distribution, and which have a
particular correlation structure. The new multivariate distribution representations are given
as single integral solutions of familiar mathematical functions which can be evaluated using
common mathematical software packages. The new approach can be used to obtain single
integral representations for the multivariate probability density function, cumulative distribution
function, and joint moments of some widely used statistical distributions in wireless
communication theory, under an assumed correlation structure. The remarkable advantage
of the new representation is that the computational burden remains at numerical evaluation
of a single integral, for a distribution with an arbitrary number of dimensions. The
new representations are used to evaluate the performance of diversity combining schemes
and multiple input multiple output systems, operating in correlated fading channels. The
new framework gives some insights into some long existing open problems in multivariate
statistical distributions. -
- Subjects / Keywords
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- Graduation date
- Fall 2010
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- Type of Item
- Thesis
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- Degree
- Master of Science
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- License
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.