Abstract
As a flexible communication manner, unmanned aerial vehicle (UAV) communication is a promising technology for wireless communication systems. Considering UAV data collection in wireless sensor network, this paper proposes a novel trajectory optimization scheme to minimize UAV’s propulsion energy consumption. The scenario of a fixed-wing UAV flying uniformly at a fixed altitude is considered. Thus the theoretical minimization model of UAV’s propulsion energy is derived based on the line-of-sight channel model and reliable communication distance. Then the minimum-degree-prior (MDP) placement algorithm for the minimum clique partitioning problem we just presented in another paper is utilized to deploy the virtual base stations (VBSs) and determine the UAV’s waypoints. The trajectory is finally optimized by leveraging the travelling salesman problem with convex optimization technique. Our scheme requires fewer virtual base stations owing to the effectiveness of MDP algorithm as compared with the scheme that first proposed the concept of VBS. The numerical results consequently show that our scheme is superior over the benchmark schemes in the minimization of UAV flight distance and propulsion energy.
This work is supported by the Fundamental Research Funds for the Central Universities (Grant No. NZ2020021), the Aeronautical Science Funds (Grant No. 2020Z073052001) and the National Natural Science Foundation of China (Grant No. 62132008).
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Xu, J., Wu, D., Yuan, J., Liu, H., Zhai, X., Liu, K. (2023). Trajectory Optimization for Propulsion Energy Minimization of UAV Data Collection. In: Li, B., Yue, L., Tao, C., Han, X., Calvanese, D., Amagasa, T. (eds) Web and Big Data. APWeb-WAIM 2022. Lecture Notes in Computer Science, vol 13421. Springer, Cham. https://doi.org/10.1007/978-3-031-25158-0_18
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