Joint optimization of resource allocation and trajectory based on user trajectory for UAV-assisted backscatter communication system

Peizhong Xie, Junjie Jiang, Ting Li, Yin Lu
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Abstract

The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables. An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method, and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.
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基于用户轨迹的无人机辅助反向散射通信系统的资源分配和轨迹联合优化
近年来,后向散射通信受到学术界和工业界的广泛关注。本文提出了一种基于用户轨迹的无人机辅助后向散射通信的资源分配和轨迹优化方法。本文将建立一个优化问题,在考虑北斗数据和工作能耗的约束条件下,基于预先估计的已知用户轨迹的大规模信道状态信号,对无人机轨迹、无人机发射功率和北斗调度进行联合优化,以实现系统能效最大化。该问题是一个分数形式的非凸优化问题,优化变量之间存在非线性耦合。基于 Dinkelbach 算法、块坐标下降法和连续凸优化技术,提出了一种迭代算法。首先,基于 Dinkelbach 方法将目标函数转换为非分数编程问题,然后利用块坐标下降法将原始复杂问题分解为三个独立的子问题。最后,采用连续凸近似法求解轨迹优化子问题。仿真结果表明,与对比方案相比,所提出的方案和算法具有明显的能效提升。
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