面向大规模物联网的无人机通信感知一体化能效优化算法OA北大核心CSTPCD

Taking into account the repetition sensing and energy limitation of UAV-enabled integrated sensing and communication in massive Internet of Things(IoT)scenarios,the authors propose a novel energy-efficient optimization scheme based on clustering algorithm.The scheme aims to maximize the energy efficiency of the UAV by jointly optimizing the UAV three-dimensional(3D)trajectory and transmit power while meeting the constraints of the mobility and sensing ability of the UAV.To deal with this non-convex optimization problem,the original problem is decomposed into two subproblems.Then,the simulated annealing algorithms and convex optimization techniques are adopted to optimize the hovering positions and flight speeds,so as to abtain the optimal trajectory of the UAV.Finally,according to the optimal trajectory,the closed-form expressions for the transmission power are derived.The proposed clustering-based energy-efficient optimization algorithm can obtain 4 times convergence speed and 20%～30%energy efficient improvement compared with the traditional two-dimensional(2D)and 3D methods.