## 4 Simulations and Analysis
This figure shows that as \(\theta_{FoV}\) increases, the communication performance first improves rapidly and then has a slight downward trend. For instance, the ergodic capacity for \(\theta_{FoV}=20\), 30, 40 mrad is 32.8, 36.4, and 36.1 bit/s/Hz when \(\sigma_{a}=10\) mrad, respectively. This is because when \(\theta_{FoV}\) is relatively low, the receiver can receive more optical signal energy, and the ergodic capacity increases rapidly as \(\theta_{FoV}\) increases. However, when \(\theta_{FoV}\) increases to the threshold, more background noise is introduced as \(\theta_{FoV}\) increases and affects the communication quality. In addition, the slight downward trend is influenced by various orientation deviations, which becomes less pronounced when the orientation deviation is higher. At the same time, orientation deviations also affect the ergodic capacity when \(\theta_{FoV}\) is low, i.e., the ergodic capacity decreases as the orientation deviation increases. When \(\theta_{FoV}=20\) mrad, the ergodic capacity for \(\sigma_{a}=10\), 15, 20, 25 mrad is 32.8, 22.3, 14.9, and 10.4 bit/s/Hz, respectively. This phenomenon is because that \(\sigma_{a}\), which represents the variance of the beam center randomly deviated from the center of receiver lens, can reduce more received beam energy, resulting in lower ergodic capacity. It is worth noting that in engineering applications of drone-assisted FSO communications, a fast, high-precision stabilization and control system is required to obtain a better communication performance, i.e., to reduce the impact of random deviation on the received optical power. Figure 6: Ergodic capacity versus \(P_{t}\) under AoA fluctuations. Figure 8 depicts the influence of \(r_{L}/r_{r}\) on the ergodic capacity for various detection techniques. Distinctly, the ergodic capacity under the heterodyne detection is higher than that under IM/DD due to the higher conversion gain and better noise-filtering performance of the heterodyne detection technique. Furthermore, for the same detection technique, the higher \(r_{L}/r_{r}\), the higher ergodic capacity, and thus the better communication performance. For instance, for the heterodyne detection technique and \(P_{t}=10\) dBm, the ergodic capacity for \(r_{L}/r_{r}=10\), 20, 30 is 25, 36, and 37.7 bit/s/Hz, respectively. Finally, the Monte Carlo results are in excellent agreement with the numerical results. In Figure 9, the ergodic capacity for varying link distances under various atmospheric conditions is depicted. Comprehensively, the higher the link distance, the worse the communication performance. For instance, for weak turbulence and \(P_{t}=2\) dBm, the ergodic capacity for \(L=1\), 2, 4 km is 35, 33.4, and 30.4 bit/s/Hz, respectively. Furthermore, the ergodic capacity declines as the deterioration of atmospheric turbulence. For instance, for \(L=1\) km and \(P_{t}=-2\) dBm, the ergodic capacity under weak turbulence is 33.7 bit/s/Hz, but it drops to 33.5 bit/s/Hz and 33.2 bit/s/Hz for moderate and strong turbulence, respectively. Finally, the simulation results are consistent and correspond well to the analytical results. Figure 8: Ergodic capacity versus \(P_{t}\) under different detection techniques and various \(r_{L}/r_{r}\). Figure 3:0 Ergodic capacity versus \(\theta_{FoV}\) under various \(\sigma_{a}\).