# Performance of UAV-to-Ground FSO Communications with APD and Pointing Errors
###### Abstract  
Recently, a combination of unmanned aerial vehicles (UAVs) and free-space optics (FSO) has been investigated as a potential method for high data-rate front-haul communication links. The aim of this work was to address the performance of UAV-to-ground station-based FSO communications in terms of the symbol error rate (SER). The system proposes utilizing subcarrier intensity modulation and an avalanche photo-diode (APD) to combat the joint effects of atmospheric turbulence conditions and pointing error due to the UAV's fluctuations. In the proposed system model, the FSO transmitter (Tx) is mounted on the UAV flying over the monitoring area, whereas the FSO receiver (Rx) is placed on either the ground or top of a high building. Unlike previous works related to this topic, we considered combined channel parameters that affect the system performance such as transmitted power, link loss, various atmospheric turbulence conditions, pointing error loss, and the total noise at the APD receiver. Numerical results have shown that, for the best system SER performance, the value of an average APD gain at the Rx can be selected, varying from 18 to 30, whereas the equivalent beam waist radius at the Tx should be in a range from 2 to 2.2 cm in order to decrease the effects from the UAV's fluctuations. unmanned aerial vehicles; free-space optics (FSO); atmospheric turbulence; pointing errors +
Footnote †: journal: Applied System  
**2021**, 4, 65. [[https://doi.org/10.3390/asst4030065](https://doi.org/10.3390/asst4030065)]([https://doi.org/10.3390/asst4030065](https://doi.org/10.3390/asst4030065))  
radiative fluctuations in the received signal, which severely degrades the performance of this communication system. UAV-based FSO communication links have been relatively well studied in the literature [6; 7; 15; 16; 17; 18; 19]. In particular, the author in [6] proposed an approach of flying platforms for relaying the FSO backhaul or front-haul data traffic from the access-to-core networks. It can be considered as a promising solution for the 5G+ cellular network. In [7], a novel FSO front-haul channel model for a UAV-based system was developed by qualifying the geometric and misalignment losses. Moreover, the authors in [15] derived accurate statistical channel models for multi-roto UAV-based FSO communication links considering the combined effect of atmospheric turbulence along with the UAV's angle-of-arrival (AoA) fluctuations. In addition, the authors in [16; 17] studied multiple UAV-based FSO systems with beam pointing ability. For instance, in [16], [PERSON] et al. adaptively studied beam divergence to reduce the parameters' requirements, such as the receive aperture diameter, transmit power and pointing. In [17], [PERSON] et al. designed a deterministic model and simulation platform for air-to-air FSO links to support multi-element optical transceiver arrays for different parameters (e.g., communication range, beam divergence, array size, beam wavelength, and platform dynamics). A tractable bit error rate (BER) expression for the FSO links based on UAV including the joint effects of the atmospheric turbulence channel together with pointing errors is provided in [18]. In [19], [PERSON] et al. studied the effects of AoA variation and pointing error simultaneously to the airborne FSO system considering the adaptive beam size control technique. In [20], [PERSON] et al. presented channel modeling, performance analysis, and parameter optimization for hovering UAV-based FSO communications. In the channel model for such a system, four types of impairments (i.e., atmospheric loss, atmospheric turbulence, pointing error and link interruption due to the angle of incidence oscillations) are considered. However, most of these works were considered the channel modeling and have not taken into account the effects of Tx's and Rx's parameters on the system performance. Most recently, the authors in [21] suggested using APD at Rx to reduce the influence of UAV fluctuations in order to improve the performance of UAV-based FSO systems.