The Fischer–Snedecor $\mathcal {F}$-Distribution Model for Turbulence-Induced Fading in Free-Space Optical Systems

Peppas, Kostas P.; Alexandropoulos, George C.; Xenos, Evangelos D.; Maras, A.M.

doi:10.1109/jlt.2019.2957327

Cited by 80 publications

(103 citation statements)

References 26 publications

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“…Traditionally, a large number of probability density functions (PDFs) have been utilized to model the received optical power of an FSO link. The most widely used and accepted PDF models include the Log-Normal (LN), Gamma-Gamma (GG), Gamma, Weibull, K, I-K, Malaga, the Fisher-Snedecor F and the negative exponential [1][2][3]. In order Technologies 2021, 9, 26 2 of 13 to evaluate the performance of an optical communication system, various link parameters can be employed, such as the probability of detection, the outage probability, the average capacity and the outage capacity [1,4].…”

Section: Introductionmentioning

confidence: 99%

RSSI Probability Density Functions Comparison Using Jensen-Shannon Divergence and Pearson Distribution

et al. 2021

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The performance of a free-space optical (FSO) communications link suffers from the deleterious effects of weather conditions and atmospheric turbulence. In order to better estimate the reliability and availability of an FSO link, a suitable distribution needs to be employed. The accuracy of this model depends strongly on the atmospheric turbulence strength which causes the scintillation effect. To this end, a variety of probability density functions were utilized to model the optical channel according to the strength of the refractive index structure parameter. Although many theoretical models have shown satisfactory performance, in reality they can significantly differ. This work employs an information theoretic method, namely the so-called Jensen–Shannon divergence, a symmetrization of the Kullback–Leibler divergence, to measure the similarity between different probability distributions. In doing so, a large experimental dataset of received signal strength measurements from a real FSO link is utilized. Additionally, the Pearson family of continuous probability distributions is also employed to determine the best fit according to the mean, standard deviation, skewness and kurtosis of the modeled data.

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Section: Introductionmentioning

confidence: 99%

RSSI Probability Density Functions Comparison Using Jensen-Shannon Divergence and Pearson Distribution

et al. 2021

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“…The plasma electron density pdf can be obtained using () and ():

f_{N_{e}} false(x false) = \frac{η}{x^{2} h^{δ}} f_{V} ((), \frac{η}{x h^{δ}}),

where

0 < x \leq \frac{η}{h^{δ} V_{0}}

. It should be observed that the distribution in () is the inverse gamma distribution, which has been proposed to model composite fading environments, that is, shadowing and multipath, and turbulent large‐scale irradiance fluctuations 10,12,13 . Figure 2 shows plots of ().…”

Section: Em Waves Through Solar Coronamentioning

confidence: 99%

“…It should be observed that the distribution in (10) is the inverse gamma distribution, which has been proposed to model composite fading environments, that is, shadowing and multipath, and turbulent large-scale irradiance fluctuations. 10,12,13 Figure 2 shows plots of (10). Since the heliocentric distances in Figure 2 correspond to near Earth's orbit, the parameters in (10) are α ¼ 1:5409, β ¼ 0:0158, V 0 ¼ 275km s À1 , η ¼ 8:6 Â 10 7 km s À1 cm À3 (Yakovlev and Yakovlev 22 ) and δ ¼ 2.…”

Section: Em Waves Through Solar Coronamentioning

confidence: 99%

“…Thus, the IGG distribution was proposed to describe composite fading channels, that is, incorporating shadowing and multipath, and was shown to be superior to both log-normal and gamma-gamma distributions. 11 Since the log-normal and gamma-gamma distributions are commonly used for deep space communications, 12,29 the IGG pdf will be compared to the proposed distribution.…”

Section: Application To Deep Space Communicationmentioning

confidence: 99%

“…10,11 Accordingly, numerous models were introduced by combining the inverse gamma, or the inverse Gaussian distributions, characterizing large-scale turbulence, with a model for small-scale turbulence, within the framework of Rytov extended theory. 1 The inverse Gaussian-gamma 11 and the Fisher-Snedecor F -distribution models 12 have ranges of validity spanning weak to strong scintillation, while the κ-μ/inverse gamma and η-μ/inverse gamma were introduced to model composite, that is, shadowing and multipath, fading channels. 13 The above pdfs show good agreement with measurements data under different near-Earth atmospheric experimental conditions.…”

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confidence: 99%

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Probability density of irradiance for Electromagnetic waves propagating through the solar corona

Shishter

2021

Int J Communication

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Summary Deep space exploration missions require the modelling of deep space communication channels. Due to the turbulent nature of space channels, propagating electromagnetic waves suffer from fading‐induced turbulence. In particular, scintillation effects are imparted on the intensity of electromagnetic beam wave propagating through the solar corona. Thus, it is imperative to determine the wave intensity distribution. Often, distributions derived and verified for terrestrial channels are applied to wave propagation through deep space channels. However, this neglects the specific nature of the physical processes in the channel. For example, to incorporate the events of solar inferior and solar superior conjunctions, the introduced statistical distribution should be valid over a large‐range, spanning weak to strong, scintillation conditions. Moreover, the solar corona physical parameters should be clearly related to the distribution parameters. Such a theoretical model can be derived based on Rytov solution, the solar wind speed distribution and the space permeating plasma electron density variation. The resultant wave intensity distribution is compared with the Rician, the Nakagami and the inverse Gaussian–gamma distributions for different scintillation conditions.

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Performance analysis of FSO communications over a generalized turbulence fading channel with pointing error

Shishter,

Ali,

Young

2024

Trans Emerging Tel Tech

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SummaryQuantitatively assessing the performance of free space optical (FSO) communication systems requires an accurate description of turbulence induced fading. However, it is well known that common irradiance distributions inaccurately model intensity tail regions. Recently, a general fading model as the product of arbitrary number of Gamma with inverse Gamma was proposed and shown to accurately predict measurements, besides containing many well‐known models as special cases. This paper is concerned with analyzing the effect of discrepancies among different fading distributions on optical system performance in terms of bit error rates and capacity. Based on the general fading model a unified analysis of the channel structure effects on FSO communications in the presence of turbulence and pointing error is presented. The outage probability is investigated for both homodyne and direct detection schemes. Closed form expressions for the average probability of bit error for intensity modulation, phase shift keying and polarization shift keying, single‐input‐single‐output systems are given and verified by Monte‐Carlo simulations. Spatial diversity is also studied through single‐input‐multiple‐output systems. Also, the ergodic capacity is derived. Comparisons between the proposed distributions and other widely used distributions are carried out and show significant differences among existing fading models. This suggests possible improvements in the spectral efficiency and error performance design of optical wireless communication systems.

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The Fischer–Snedecor $\mathcal {F}$-Distribution Model for Turbulence-Induced Fading in Free-Space Optical Systems

Cited by 80 publications

References 26 publications

RSSI Probability Density Functions Comparison Using Jensen-Shannon Divergence and Pearson Distribution

RSSI Probability Density Functions Comparison Using Jensen-Shannon Divergence and Pearson Distribution

Probability density of irradiance for Electromagnetic waves propagating through the solar corona

Performance analysis of FSO communications over a generalized turbulence fading channel with pointing error

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