# Data Traffic Modeling in RPAS/UAV Networks with Different Architectures
## 2 Related Works
An important question is whether an existing cellular network designed for terrestrial users can also effectively cover new UAV users in three-dimensional (3D) space for both uplink and downlink. In practice, there are problems of terrestrial communications interference and a non-uniform three-dimensional antenna gain pattern of a terrestrial base station. The article presents a new 3D model of the system, taking into account UAV users, which offers an analytical basis for determining the characteristics of their 3D uplink/downlink coverage. A 3D analysis of the coverage was carried out taking into account the key parameters of the system, such as the cell load factor, the tilt of the ground base station antenna, the UAV height and the antenna beam width. Potential 5G beneficiaries and network use are considered in [21]. Three main use cases are considered: Vehicle-to-Vehicle communications, drones, and healthcare. The challenges and disadvantages of current cellular technologies have been investigated and highlighted in relation to these use cases, and ways to overcome these disadvantages in 5G networks have been identified. UAVs as a component of the IoT can provide sensing and communications in the air due to their advantages in mobility and flexibility. However, the cellular QoS between the UAV and the base station cannot be guaranteed when the UAVs are at the edge of a cell or are experiencing deep fading. The article [22] considers the non-cooperative cellular Internet of the UAV and proposes a joint data transfer protocol, in which the UAV can download sensor data using the UAV relay to provide a better quality of communication service for sensing tasks. The design of the trajectory and control of radio resources that support the joint cellular Internet of the UAV are considered. The RPAS/UAV communication requirements must be assessed in the context of an Air Traffic Control (ATC) function [23] (Figure 1). Modeling of channels for UAV communication over cellular networks has been considered in a number of works, since UAV communication is an emerging and underexplored field. Accurate channel parameters are critical to optimizing performance and designing effective UAV communications. Models of path loss and shadowing indicators for a radio channel between UAVs and cellular networks are given in [24]. It is shown that the exponent of path losses decreases as the UAV moves upward, approaching propagation in free space for horizontal distances of up to tens of kilometers at an UAV height of about 100 m.  
An overview of the measurement methods proposed for modeling UAV channels using low-altitude platforms, as well as attempts to determine the channel characteristics, is given in [25]. The review also discusses approaches to modeling UAV channels from a modern point of view. A new Coordinate Multipoint (CoMP) based network architecture for UAV-assisted wireless communications is proposed in [26]. The high mobility of the UAV is used to achieve effective multi-user communication with several UAVs and to reduce interference. The placement and movement of the UAV is optimized using the theory of random matrices. A new structure for a UAV network with the possibility of mass access, supported by Non-Orthogonal Multiple Access (NOMA), is proposed in [27]. The performance assessment of UAV networks with NOMA is carried out, using stochastic geometry to simulate the position of UAVs and ground users. The joint design of the trajectory and the power distribution for static NOMA users based on a simplified 2D model of a UAV flying at a fixed altitude is investigated. The problem of UAV placement is solved using machine learning methods, when ground users are in roaming, and the UAVs are able to accordingly change their position in three dimensions. A secured UAV-assisted heterogeneous network environment and seamless Internet protocol prototype is proposed in [28]. UAVs are controlled over the Internet to remove communication barriers over long distances and improve remote sensing.