# Coverage Strategy for Small-Cell UAV-Based Networks in IoT Environment
## 2 Related Works
The paper addresses the challenge of improving the energy efficiency and communication reliability of IoT networks by using UAVs as relays for power and data transmission. The authors propose a novel power-splitting relaying protocol that enables efficient energy harvesting by IoT devices while maintaining a reliable communication link with the UAV relays. The proposed protocol uses NOMA technology to allow multiple IoT devices to share the same frequency and time resources for communication, while the UAVs serve as relays for both power and data transmission. The power-splitting relaying protocol divides the signal received by each UAV into two parts: one for energy harvesting and the other for forwarding data to the IoT devices. The authors also consider the impact of interference and path loss on the performance of the network, and propose a joint power allocation and user grouping algorithm to optimize the performance of the system. The paper presents simulation results that demonstrate the effectiveness of the proposed power-splitting relaying protocol in improving the energy efficiency and communication reliability of the NOMA-IoT network with multiple UAVs compared with other existing protocols. The authors also discuss the potential applications of their work in areas such as smart cities, smart agriculture, and environmental monitoring. [PERSON] et al. [26] propose a strategic and cost-effective solution for the deployment of unmanned aerial vehicle (UAV)-based flying access networks. The paper addresses the challenge of providing reliable and cost-effective wireless connectivity in areas with limited or no traditional infrastructure, such as rural or disaster-stricken regions. The authors propose a solution that involves deploying a fleet of UAVs equipped with wireless access points to provide connectivity to ground users. The proposed solution uses game theory to model the interactions between the UAVs and the ground users and optimizes the deployment strategy to achieve a balance between the availability and cost of the network. Specifically, the authors use s-modular game analysis, a variant of game theory, to model the strategic interactions between the UAVs and ground users in terms of availability and cost. [PERSON] et al. [27] propose a fuzzy logic-based solution for efficient UAV positioning in an Internet of Things (IoT) environment for data collection. The paper addresses the challenge of efficiently collecting data from IoT devices located in a wide area using a UAV as a data collector. The authors propose a fuzzy logic-based approach to determine the optimal position of the UAV for data collection, taking into account factors such as the number of IoT devices, the distance between the UAV and the devices, and the data transfer rate. The proposed solution involves designing a fuzzy logic controller that takes inputs such as the number of IoT devices, the distance between the UAV and the devices, and the data transfer rate and outputs the optimal position of the UAV for data collection. The authors also use a genetic algorithm to optimize the fuzzy logic controller parameters. As a solution to jointly optimizing the power allocation and 3D trajectory of a UAV in a wirelessly powered communication network with obstacles, the authors of [28] consider a scenario where a UAV is used as a mobile base station to provide wireless power transfer and communication services to ground users. The UAV is equipped with a wireless power transmitter and a communication antenna, and it moves along a 3D trajectory to serve users in the coverage area. However, the presence of obstacles in the environment can cause signal attenuation and interference, which affect the UAV's performance. To address these challenges, the authors propose a joint power-and-3D-trajectory optimization scheme that takes into account the impact of obstacles on the UAV's performance.