Connectivity-aware trajectory design for unmanned aerial vehicles over cellular networks

Abstract

Driven by the growing popularity of unmanned aerial vehicles (UAVs), how to ensure effective wireless communications for UAVs has attracted significant attention recently. While current UAVs mainly rely on simple point-to-point communication over the unlicensed band, connecting UAVs to cellular networks is promising to support real-time, reliable, secure and beyond-visual-line-of-sight data transmission between UAVs and ground control stations. However, cellular networks are primarily optimized for terrestrial users, and are thus limited in providing the seamless aerial coverage. In this thesis, we present a connectivity-aware trajectory design method to guarantee a UAV’s effective connectivity over cellular networks. This study is motivated by the fact that, instead of looking into expensive network upgrades, we can exploit the unique controllable 3-D mobility of UAV users to satisfy communication requirements. Moreover, by utilizing theories and tools from both the areas of communications and robotics, we attempt to create intersections between these two communities in the research of UAVs through this study. To this end, firstly, we investigate the fundamental characteristics of aerial coverage provided by ground cellular infrastructures in urban environments. This is achieved by reconstructing realistic radio maps for UAVs via ray-tracing simulations, which allow us to exploit fine building geometry in modeling propagation channels between UAVs and ground base stations. Secondly, given a realistic aerial radio map to capture the complicated propagation environments, we investigate a 3-D connectivity-aware UAV path planning problem. Specifically, considering a UAV taking long-range missions, we aim to minimize its path length while satisfying specific communication requirements. To explicitly impose communication requirements on UAV path planning, two new metrics are introduced to quantify the cellular connectivity of a UAV path. We formulate the 3-D path planning problem as finding the shortest path given connectivity constraints. Then, based on graph search methods, we propose a novel algorithm to solve the problem efficiently. The proposed approach returns a sequence of 3-D waypoint positions that navigate the UAV between the predetermined source and destination location pair. We validate the effectiveness of our proposed algorithms on aerial coverage maps of an urban area in Rosslyn, Virginia. The simulation results show that our path planning scheme achieves a significant gain in connectivity performance, compared with the baseline methods. Thirdly, by taking the results of waypoints from the path planning to generate a smooth and flyable trajectory, we study a method to model realistic 3-D UAV operations in mobility scenarios for evaluation of the mobility performance of aerial users in cellular networks. A case study is provided to illustrate how to apply this simulation method to evaluate mobility performance of cellular-connected UAVs with different flight plans in the context of real-world applications. The experimental results not only show the capability of the proposed mobility modelling and simulation method, but again demonstrate the performance gain of the developed connectivity-aware flight plan scheme.