Abstract
In this paper the exact probability density function of a multivariate α-μ distributed variables with exponentially correlated random variables is derived. Capitalizing on this the joint probability density function (JPDF) is derived for the square ratios of two multivariate exponentially correlated α-μ distributed variables. Closed form expressions are determined for the cumulative distribution function (CDF) and probability density function (PDF) of the maximal and minimal square ratio of two multivariate exponentially correlated α-μ distributions. Using these new formulae, SIR (signal-to-interference) based analysis of selection combining (SC) receiver through standard communication system performance measures can be performed.
| Original language | English |
|---|---|
| Pages (from-to) | 152-159 |
| Number of pages | 8 |
| Journal | Mathematical and Computer Modelling |
| Volume | 54 |
| Issue number | 1-2 |
| DOIs | |
| Publication status | Published - 1 Jul 2011 |
| Externally published | Yes |
Keywords
- Maximal and minimal square ratios
- Multivariate distribution
- SIR based SC diversity
- Square ratios of exponentially correlated variables
ASJC Scopus subject areas
- Modelling and Simulation
- Computer Science Applications
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Cite this
Milovanović, G. V., Stefanović, M. Č., Panić, S. R., Anastasov, J. A., & Krstić, D. S. (2011). Statistical analysis of the square ratio of two multivariate exponentially correlated α-μ distributions and its application in telecommunications. Mathematical and Computer Modelling, 54(1-2), 152-159. https://doi.org/10.1016/j.mcm.2011.01.046