Looking before Crossing: An Optimal Algorithm to Minimize UAV Energy by Speed Scheduling with a Practical Flight Energy Model
Feng Shan, Junzhou Luo, Runqun Xiong, Wenjia Wu, Jiashuo Li
Abstract
Unmanned aerial vehicles (UAVs) are being widely used in wireless communication, e.g., collecting data from ground nodes (GNs), where energy is critical. Existing works combine speed scheduling, i.e., the controlling of speed, with trajectory design for UAVs, making it complicated to solve while loses focus on the fundamental nature of speed scheduling. We focus on speed scheduling by considering straight line flights, with applications in monitoring power transmission lines, roads, water/oil/gas pipes and rivers/coasts. By real-world flight tests, we disclose a speed-related flight energy consumption model, distinct from typical distance-related or duration-related models. Based on such a practical energy model, we develop the looking before crossing (virtual rooms) algorithm, where virtual rooms on the time-distance diagram represent the spatio-temporal constraint of GNs in wireless transmission. This algorithm is proved to be optimal in solving the offline problem, where all information is known before scheduling. For the online problem, i.e., GN information is not unavailable unless flies close, we propose an offline-inspired online heuristic. Simulation shows its performance is near the offline optimal. Our study on the practical flight energy model and speed scheduling sheds light on a new research direction on UAV-aided wireless communication.