# Probabilistic Modeling of Dust-Induced FSO Attenuation for 5G/6G Backhaul in Arid Regions
## 2 Experimental Setup  
The experimental system consists of a rectangular dust chamber with dimensions of 90 cm \(\times\) 40 cm \(\times\) 40 cm, as shown in Figure 1, designed to emulate dusty atmospheric conditions in a repeatable manner. The dust sample used in this study was collected from a real dust storm event. The particle size distribution was analyzed using a particle size analyzer (SALD 2300, Shimadzu Corporation, Kyoto, Japan), which indicated a Lognormal distribution with a mean diameter of 17.3 um and a standard deviation of 11.7 um. Fans were installed to blow up the dust after injection, and uncoated precision windows (with a loss of \(\sim\)4% per surface) were used to transmit optical signals. Two single-mode fiber-coupled laser diodes (LDs) were used: a 1550 nm LD (Keysight, Santa Rosa, CA, USA, N7714A) with 4 mW output power for the primary FSO link and a 520 nm Fabry-Perot LD (Thorlabs, Newton, NJ, USA) for visibility measurements. Each beam was collimated using aspheric lens collimators, and the received optical power was detected using Thorlabs photodiodes (PDs) (S122C for the 1550 nm LD and S120C for the 520 nm LD) with \(-\)43 dBm sensitivity connected to a Thorlabs PM320E power meter. The S120C and S122C PD power sensors offer a typical measurement accuracy of \(\pm\)5% and resolutions of 1 nW and 2 nW, respectively. These specifications, combined with built-in shielding and a large sensor aperture, support high precision and stability in detecting low-power optical signals such as those used in our experiments. The received signal power was recorded during eight independent measurement sessions, each conducted under identical controlled conditions to ensure consistency. Data acquisition was performed every 0.1 s without applying temporal averaging, which yielded a high-resolution time series that captured the complete decay of airborne dust in the chamber. Each session lasted approximately 40 min, continuing until the particles had settled completely. To eliminate ambient light interference, all experiments were conducted in a dark room. The resulting data were stored in CSV format for further analysis. During preprocessing, a small number of 'NaN' (Not a Number), caused by occasional sensor read interruptions, were detected and removed programmatically. These instances were rare and did not affect the overall statistical integrity of the dataset. Additional extreme or aberrant values were not observed. The cleaned dataset was then used for the fitting of the probabilistic distribution and modeling. The experiments were conducted in a dark room to eliminate ambient light noise. This process was repeated eight times under identical conditions to ensure consistency across measurements and to collect sufficient data for robust probabilistic model fitting. To assess repeatability, we evaluated the attenuation statistics within a fixed visibility bin centered at 500 m (\(\pm\)25 m) across all eight sessions. The specific attenuation values showed consistent behavior across sessions, with mean values ranging from 138.2 to 149.8 dB/kmand standard deviations between 14.1 and 16.0 dB/km. These results demonstrate that the measurements remained stable and reproducible under equivalent dust conditions. The signal attenuation was calculated using the dataset for the 1550 nm FSO link. The severity of dust storms can be classified based on the visibility range, defined as the maximum distance at which objects can be distinguished. Visibility was estimated from the 520 nm measurements and used to classify attenuation into three visibility categories: dense dust (visibility \(<\) 200 m), moderate dust (200 m \(\leq\) visibility \(\leq\) 1 km), and light dust (visibility \(>\) 1 km). This classification is based on widely accepted meteorological standards and their relevance to real-world dust storm scenarios in arid regions.