# 3D Global Path Planning Optimization for Cellular-Connected UAVs under Link Reliability Constraint
## 1 Introduction
### Motivation and Contributions  
As discussed above, one of the critical challenges to enhance BVLOS flight safety is the lack of reliable and ubiquitous aerial wireless communication systems. Motivated by the distinctive features of existing cellular networks, partially provided aerial coverage, adaptability of UAVs, and the important role of global path planning approaches to facilitate path planning for autonomous UAV operations, this paper proposes a practical method to find a 3D collision-free global path for UAVs operating BVLOS.  
The objectives of the path planning optimization problem are to minimize the flight distance and maximize the cellular link reliability while satisfying real-world constraints, such as power consumption and permitted flight height. The key contributions of this work can be summarized as follows:  
* A reliable aerial 4G coverage zone for UAV communications in suburban environments has been proposed. The reliable zone has been identified based on the statistical analysis of 4G key performance indicators (KPIs), such as reference signal received power (RSRP), reference signal received quality (RSRQ), and the number of handovers, which have been extensively measured in a suburban environment.
* A cumulative objective function has been developed for the 3D UAV path planning optimization. The objective function consists of the length of the total path, the length of the reliable path, and a set of penalty functions for cases where the path collides with the obstacles and passes from the forbidden zones. Furthermore, other real-world constraints, such as maximum and minimum permitted flight height and power constraints, have been applied to the optimization problem.
* The performance of the proposed UAV path planning method has been investigated by utilizing different intelligent optimization algorithms, such as particle swarm optimization (PSO) and genetic algorithm (GA), and a combination of both algorithms, PSO-GA. Furthermore, the performances of the considered optimization algorithms for solving 3D path planning problems have been investigated under different scenarios.
* The ability of the proposed strategy to solve real-world 3D path planning problems is validated by comparing the simulation results with the aerial drive test results. The comparison results prove that the proposed strategy can provide a stable and valid global optimal solution for UAV path planning in suburban environments.  
The remainder of this paper is organized as follows: A review of recent related works is presented in Section 2. Section 3 describes the proposed UAV path planning strategy and research methodology, including the measurement method, identifying reliable cellular network aerial coverage, as well as defining the path planning problem, objective functions, search space, and constraints. Section 4 presents the measurement results of the aerial drive test in a 4G network and discusses the reliable aerial coverage. Next, the simulation results of the path planning optimization under different scenarios are discussed. Then, the performance of the proposed strategy is validated by comparing the simulation results with the aerial drive test results. Finally, Section 5 concludes the paper.