Abstract

In this article we propose the use of the so-called Fisher-Snedecor $\mathcal {F}$ -distribution to model atmospheric turbulence-induced fading in free space optical communication systems. The proposed model is a two-parameter distribution, defined as the ratio of two independent gamma random variables. In this context, the proposed model is based on a doubly stochastic theory of turbulence-induced fading, assuming that small-scale irradiance variations of the propagating wave, modeled by a gamma distribution, are a subject to large-scale irradiance fluctuations, modeled by an inverse gamma distribution. It is shown that the $\mathcal {F}$ -distribution yields at least as good, or even a better fit to experimental and computer simulation data as compared to the well known gamma-gamma distribution. Also, important statistical measures such as cumulative distribution function (CDF) and moment generating function (MGF) are mathematically simpler than those of the gamma-gamma distribution. Motivated by these facts, the performance of single-input—multiple output (SIMO) and multiple-input—multiple output (MIMO) systems operating in the presence of $\mathcal {F}$ turbulence is assessed. The proposed analysis is substantiated by numerically evaluated results and Monte Carlo simulations.

Irradiance probability density function for turbulence induced fading in free space optics

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J. Opt. Soc. Am. A 39(7) 1267-1274 (2022)

Inverse Gaussian gamma distribution model for turbulence-induced fading in free-space optical communication

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Appl. Opt. 57(12) 3031-3037 (2018)

General statistical model of irradiance fluctuations in free space optics

Yousef M. Shishter, Rupert Young, and Falah H. Ali
J. Opt. Soc. Am. A 40(1) 53-63 (2023)

Adaptive selective relaying in cooperative free-space optical systems over atmospheric turbulence and misalignment fading channels

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Opt. Express 22(13) 16629-16644 (2014)

Performance of dual-hop FSO/RF systems with fixed-gain relaying over Fisher–Snedecor F and κ-μ shadowed fading channels

Junrong Ding, Xiaolong Xie, Ling Wang, Liying Tan, Jing Ma, and Dongpeng Kang
Appl. Opt. 61(8) 2079-2088 (2022)