## 1 Introduction  
Future communications already benefit from free space optical (FSO) communication because of its large communication capacity, cost-effectiveness, ease of deployment, and high security [1]. FSO communication is often used to handle the \"last mile\" communication issue, especially in some dense areas [2]. Drones are already the preferred option as a relay or terminal due to their distinct mobility and line-of-sight (LOS) propagation [3, 4]. Drone-assisted FSO communication is therefore frequently used in maritime rescue [5], post-disaster emergency communication [6], military reconnaissance [7], and other applications. Pioneering work has been done on drone-assisted FSO communication systems [8]. The serial FSO decode-and-forward relay system based on hovering unmanned aerial vehicles (UAVs) was optimized by [PERSON] et al. to achieve optimal communication performance [9]. A ground-to-UAV FSO link was built to demonstrate that increasing the total received optical area and field of view (FoV) can reduce the average bit error rate (BER) [10]. Additionally, [PERSON] et al. designed a satellite-to-UAV downlink FSO links and noted out that pointing errors can reduce the average fade duration [11]. [PERSON] et al. investigated the statistical behavior of the FSO link between the hovering UAV and terminal by considering random displacement of the UAV [12]. However, drone-assisted FSO communication is vulnerable to atmospheric turbulence and pointing errors. Changes in light intensity and phase are caused by atmospheric turbulence due to temperature, humidity, pressure, etc. Several fading distributions, including log-normal distribution [13], Gamma-Gamma distribution [14], Double-Weibull distribution [15], and others, have been proposed to characterize the influence of atmospheric turbulence on the FSO link. Although the above statistical models are highly accurate under specific conditions, log-normal distribution neglects the behavior in the tails [16]. Gamma-Gamma and Double-Weibull distributions are only accurate under the weak and moderate turbulence conditions. Recently, a universal statistical distribution called the Malaga distribution was proposed by [17], which could model weak-to-strong turbulence. [PERSON] et al. conducted an investigation of the FSO link over the Malaga channel model and indicated that the Malaga distribution has higher accuracy than other distributions [18]. Apart from atmospheric turbulence, pointing errors can also degrade communication quality, which refers to the misalignment of beams caused by the hovering of the drone and the thermal expansion of the building. Much effort was devoted to exploring the inevitable pointing errors in statistical models of FSO links [19; 20]. Considering the pointing errors, the exact closed-form formulae for the average BER as well as the ergodic capacity for the relay-assisted FSO system were derived. The deterioration in communication performance was justified [19]. Thus, it is necessary to investigate the impacts of various factors, such as atmospheric turbulence and pointing errors, on the performance of drone-assisted FSO communication systems. [PERSON] et al. researched the UAV-assisted FSO communication system under atmospheric attenuation, atmospheric turbulence, and misalignment loss using the indirect modulation/direct detection (IM/DD) technique concerning the outage probability and the ergodic capacity [12]. Similarly, the FSO communication system subject to atmospheric attenuation, atmospheric turbulence, and pointing errors was developed by [PERSON] et al. to evaluate the outage probability of the communication system with the IM/DD technique [21]. Considering path loss, atmospheric turbulence, pointing errors, and geometric expansion, the outage probability of a coherent FSO communication system with the IM/DD technique was evaluated in [22]. According to the previous discussions, the impact of atmospheric turbulence along with pointing errors on drone-aided FSO systems was investigated in detail.