# Probabilistic Modeling of Dust-Induced FSO Attenuation for 5G/6G Backhaul in Arid Regions
###### Abstract  
Free-Space Optical (FSO) communication systems operating in arid regions, especially those envisioned for current and future 5G/6G networks, are significantly affected by dust storms, which causes signal attenuation and service disruptions. While previous studies have proposed deterministic models to characterize attenuation in both controlled and real environments, probabilistic modeling approaches remain largely unexplored, particularly for capturing the variability of FSO signal attenuation under dust conditions. This study proposes a probabilistic model for FSO signal attenuation developed from experiments conducted in a repeatable and well-characterized controlled dust chamber. The chamber-  
by absorption and scattering caused by weather phenomena such as turbulence, fog, rain, snow, and dust storms [6; 7]. Among these, fog and dust are particularly detrimental due to having particle sizes comparable to the optical wavelength, leading to severe scattering. These environmental factors can significantly affect signal quality, link availability, and throughput, especially in arid and semi-arid regions where dust storms are frequent and visibility fluctuates rapidly [8; 9]. Several probabilistic models have been proposed to analyze the behavior of the FSO channel under conditions of turbulence and fog. Turbulence is typically modeled based on its severity using statistical distributions such as the Lognormal, Gamma-Gamma, and Malaga distributions [10; 11]. These models capture the statistical variation of the intensity of the received signal due to fluctuations in the refractive index. On the other hand, the available literature is limited on the probabilistic modeling of FSO links under fog conditions. In [12], the authors modeled the FSO channel using the Kumaraswamy distribution, identifying it as a suitable candidate for characterizing attenuation under settled continental fog scenarios. In [13], the Johnson SB distribution was employed to model signal attenuation under varying fog severity levels, demonstrating its flexibility in capturing different atmospheric conditions. Despite the growing deployment of FSO systems in regions prone to dust storms, there remains a notable lack of standardized models specifically addressing dust-induced attenuation in optical wireless communication. While standardization bodies such as the International Telecommunication Union Radiocommunication Sector (ITU-R) have published models for attenuation due to fog, rain, and turbulence [14], these guidelines do not comprehensively account for dust-related impairments in FSO links. This gap poses challenges for system designers who require accurate link budget estimates and risk assessments in dusty environments. By developing a data-driven probabilistic model validated through controlled measurements, this study contributes toward addressing this modeling gap and offers a basis for future standardization efforts. The propagation challenges faced by FSO links in dusty environments bear a resemblance to those encountered in radio-frequency (RF) systems operating at millimeter-wave and terahertz frequencies. In both domains, particulate matter such as dust alters the propagation characteristics through absorption and scattering, leading to signal attenuation and distortion. In RF systems, especially those operating at millimeter-wave and terahertz frequencies, dust affects propagation through absorption and changes in dielectric properties. Deterministic models such as ITU-R P.840 have been used in RF domains to estimate atmospheric impairments [15]. In the context of FSO communication, research on modeling the FSO channel under dust storm conditions remains at an early stage. In our previous work [16], we introduced a deterministic model for FSO link attenuation based on visibility range during dust storms.