# Unified Performance Analysis of Direct Air-to-Underwater RF/UWOC Systems
## 2 System and Channel Models
In order to study the influence of parameters in the distribution of base stations on the outage probability of system, Figure 3 analyzes the relationship between different parameter values and outage probability when using BS distribution. From the figure, it can be seen that when the parameters of the distribution \(\alpha_{0}=0.51\), \(\beta=2.73\), the probability of power outage can reach \(10^{-7}\), which can be said to be very small. When \(\alpha_{0}=0.25\), \(\beta=2.1\), the outage probability can reach \(10^{-5}\). When \(\alpha_{0}=0.51\), \(\beta=2.1\), the outage probability can reach \(10^{-4}\). From the figure, it can be seen that as the parameter increases, the outage probability value increases. As the parameter value \(b\) increases, the outage probability decreases. This is because as the parameters change, the water surface fluctuates, leading to changes in signal stability. The parameter \(w\) of the EGG distribution determines which of the exponential and gamma distributions dominates the EGG distribution. Figure 4 shows the effect of the parameter \(w\) of the EGG distribution on the BER of the system, which decreases as the parameter \(w\) increases. In addition, it can be seen that different turbulence intensities can cause significant changes in BER, and turbulence channels also have a significant impact on the performance of the system. When the average signal-to-noise ratio of \(\alpha-\mu\) distribution is 20 dB and \(w=0.225\), the probability of power outage can reach \(10^{-4}\). When \(w=0.502\), the outage probability can the outage probability can reach \(10^{-5}\), and when \(w=0.819\), the outage probability can reach \(10^{-6}\). This is because the parameters of \(w\) change, resulting in a change in the role of exponential and gamma distributions in the EGG distribution. To investigate the impact of fog conditions on the system BER, Figure 5 shows the effect of fog conditions on the BER of the system. From the figure, it can be seen that as the concentration of fog increases, the BER of the system increases. It is obvious that higher fog concentrations will increase the absorption and scattering of light, leading to weaker optical signals and thus affecting the BER. In addition, we can also conclude that \(\mathcal{F}\) distribution is more suitable for the RF link. When the signal-to-noise ratio is 20 dB, the value of moderate fog is 6.37, and the value of light fog is 4.70. At this time, under moderate  
Figure 4: The relationship between parameters of the system w and BER. fog conditions, the BER value of the \(\mathcal{F}\) distribution exceeds \(10^{-5}\), while the error rate value of the \(\mathcal{F}\) distribution under mild fog is close to \(10^{-4}\). Light fog has a lower concentration of moderate fog compared to moderate fog, resulting in less absorption and scattering of signals, better signal reliability and stability, and better system performance. Comparing the Monte Carlo simulation with the numerical results, the simulated photon number is \(10^{4}\). From the figure, it can be seen that the simulation results are in good agreement with the numerical results. Figure 6 shows the effect of parameter \(A_{0}\) of the pointing error on the system BER. Assuming that all average signal-to-noise ratios are equal and parameter \(c\) is a positive integer, it can be observed from the graph that as \(A_{0}\) increases, the error rate shows a decreasing trend. At this point, for convenience, \(c=1\), \(w=0.0035\), \(A_{0}=1.67\), and \(A_{0}=2.34\). From the figure, it can be seen that when the distribution function of the atmospheric turbulence channel is \(\mathcal{F}\) distribution, under the condition of \(A_{0}=1.67\) and a signal-to-noise ratio of \(10\) dB, the BER of the system can reach about \(10^{-4}\). Under the condition of \(A_{0}=2.34\) and a signal-to-noise ratio of \(10\) dB, the BER of the system can reach about \(9\times 10^{-5}\). It can be seen that as the parameter \(A_{0}\) of the pointing error increases, the error rate decreases.