3D-Map Assisted UAV Trajectory Design Under Cellular Connectivity Constraints

Cellular connected unmanned aerial vehicles (UAVs) that can operate safely in beyond visual line of sight conditions are expected to open important future opportunities in the areas of transportation, goods delivery, and system monitoring. A key challenge in this area lies in the design of trajectories which, while allowing the completion of the UAV mission, can guarantee reliable cellular connectivity all along the path. Previous approaches in this domain have considered either simplistic propagation model assumptions (e.g. Line of Sight based) or more advanced models but with computationally demanding optimization solutions. In this paper, we propose a novel approach for trajectory design using a coverage map that can be obtained with a combination of a 3D map of the environment and radio propagation models. Leveraging on the convexity of subregions within the coverage map, we propose a low-complexity graph based algorithm which is shown to achieve quasi-optimal performance at a fraction of the computational cost of known optimal methods.