Gaussian Class Multivariate Weibull Distributions: Theory and Applications in Fading Channels

Sagias, N.C.; Karagiannidis, George K.

doi:10.1109/tit.2005.855598

Cited by 216 publications

(155 citation statements)

References 41 publications

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“…As a consequence, (5) (9) Moreover, the corresponding average SNR is ex- Note here that for Q1 = Q2 = Q3 = , (7) agrees with the analysis presented in [13] for the multivariate Weibull distribution with constant correlation and for identical average powers. (10) where dT,e =1 +r//3 with r taking non-negative values.…”

Section: Introductionsupporting

confidence: 85%

“…Additionally, in [12], it was argued that the Weibull distribution could also been considered as a more generic channel model for land-mobile satellite systems. In a recent paper [13], the joint PDF, CDF and the moment-generating function (MGF) for the bivariate Weibull distribution have been analytically presented. The multivariate Weibull distribution has also been studied for the exponential and the constant correlation case with equal average fading powers.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, this is the subject of our paper, whereby we apply the developed analytical framework to the performance evaluation of a 3-branch SC receiver. where Xe and Ye are the Gaussian in-phase and quadrature elements of the multipath components [13] and j is the imaginary operator. By representing Ze as the magnitude of he, i.e., Ze = Ihe , where denotes absolute value, Ze can be expressed as a power transformation of a Rayleigh distributed random variable (RV) R= £ X + jY£ as [14] Zf = Rt2s.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Trivariate Weibull Distribution with Arbitrary Correlation

Papadimitriou

Sagias

Bithas

et al. 2006

2006 International Workshop on Satellite and Space Communications

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Abstract-In this paper an anlytical framework for analyzing the arbitrarily correlated trivariate Weibull distribution is introduced. For this distribution infinite series representations for the joint probability density function, the cumulative distribution function (CDF) and the moments are derived. Two special correlation cases of the distribution are studied: the exponential and the constant. These series representations are readily applicable to the performance analysis of a 3-branch selection combining (SC) receiver operating in a Weibull correlation fading environment and the outage probability is derived. The proposed mathematical analysis is complemented by various numerical results, showing the effects of fading severity, correlation and the power decay factor.

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Section: Introductionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Trivariate Weibull Distribution with Arbitrary Correlation

Papadimitriou

Sagias

Bithas

et al. 2006

2006 International Workshop on Satellite and Space Communications

View full text Add to dashboard Cite

show abstract

“…Takođe, usled veće fleksibilnosti, Nakagami-q model obezbeđuje bo-lje podudaranje analitičkih rezultata sa eksperimentalnim, tj. izmerenim vrednostima u odnosu na Rayleigh-ev model [3].…”

Section: Uvodunclassified

“…Analitički izraz za gustinu verovatnoće predstavljen je u zatvorenom obliku, dok analitički izrazi ostalih parametara predstavljeni su u vidu beskonačnog reda. TEHNIKA -ELEKTROTEHNIKA 66 (2017) 1 2. α-q MODEL FEDINGA Ako sa r(t) označimo trenutnu vrednost amplitude procesa predstavljenog Nakagami-q modelom, sledi da je [3] (2) gde je I0(·) modifikovana Bessel-ova funkcija prve vrste nultog reda, dok je q parametar koji može imati vrednost iz opsega od 0 do 1.…”

Section: Uvodunclassified