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 |
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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
Cite this
Statistical analysis of the square ratio of two multivariate exponentially correlated α-μ distributions and its application in telecommunications. / Milovanović, Gradimir V.; Stefanović, Mihajlo Č; Panić, Stefan R.; Anastasov, Jelena A.; Krstić, Dragana S.
In: Mathematical and Computer Modelling, Vol. 54, No. 1-2, 01.07.2011, p. 152-159.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Statistical analysis of the square ratio of two multivariate exponentially correlated α-μ distributions and its application in telecommunications
AU - Milovanović, Gradimir V.
AU - Stefanović, Mihajlo Č
AU - Panić, Stefan R.
AU - Anastasov, Jelena A.
AU - Krstić, Dragana S.
PY - 2011/7/1
Y1 - 2011/7/1
N2 - 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.
AB - 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.
KW - Maximal and minimal square ratios
KW - Multivariate distribution
KW - SIR based SC diversity
KW - Square ratios of exponentially correlated variables
UR - http://www.scopus.com/inward/record.url?scp=79955471356&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79955471356&partnerID=8YFLogxK
U2 - 10.1016/j.mcm.2011.01.046
DO - 10.1016/j.mcm.2011.01.046
M3 - Article
AN - SCOPUS:79955471356
VL - 54
SP - 152
EP - 159
JO - Mathematical and Computer Modelling
JF - Mathematical and Computer Modelling
SN - 0895-7177
IS - 1-2
ER -