This paper investigates unmanned aerial vehicle (UAV)-aided backscatter communication (BackCom) networks, where the UAV is leveraged to help the backscatter device (BD) forward signals to the receiver. Based on the presence or absence of a direct link between BD and receiver, two protocols, namely transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR) protocol, are proposed to utilize the UAV to assist the BD. In particular, we formulate the system throughput maximization problems for the two protocols by jointly optimizing the time allocation, reflection coefficient and UAV trajectory. Different static/dynamic circuit power consumption models for the two protocols are analyzed. The resulting optimization problems are shown to be non-convex, which are challenging to solve. We first consider the dynamic circuit power consumption model, and decompose the original problems into three sub-problems, namely time allocation optimization with fixed UAV trajectory and reflection coefficient, reflection coefficient optimization with fixed UAV trajectory and time allocation, and UAV trajectory optimization with fixed reflection coefficient and time allocation. Then, an efficient iterative algorithm is proposed for both protocols by leveraging the block coordinate descent method and successive convex approximation (SCA) techniques. In addition, for the static circuit power consumption model, we obtain the optimal time allocation with a given reflection coefficient and UAV trajectory and the optimal reflection coefficient with low computational complexity by using the Lagrangian dual method. Simulation results show that the proposed protocols are able to achieve significant throughput gains over the compared benchmarks.

中文翻译：

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无人机辅助反向散射通信网络的吞吐量最大化

本文研究了无人机 (UAV) 辅助的反向散射通信 (BackCom) 网络，其中利用无人机帮助反向散射设备 (BD) 将信号转发到接收器。基于BD和接收器之间是否存在直接链路，提出了两种协议，即传输反向散射（TB）协议和传输反向散射中继（TBR）协议，以利用无人机辅助BD。特别是，我们通过联合优化时间分配、反射系数和无人机轨迹，为两种协议制定了系统吞吐量最大化问题。分析了两种协议的不同静态/动态电路功耗模型。由此产生的优化问题被证明是非凸的，这很难解决。我们首先考虑动态电路功耗模型，将原始问题分解为三个子问题，即固定无人机轨迹和反射系数的时间分配优化，固定无人机轨迹和时间分配的反射系数优化，以及固定无人机轨迹优化。反射系数和时间分配。然后，通过利用块坐标下降法和逐次凸逼近 (SCA) 技术，为这两种协议提出了一种有效的迭代算法。此外，对于静态电路功耗模型，我们通过使用拉格朗日对偶方法获得了给定反射系数和无人机轨迹的最佳时间分配和计算复杂度低的最佳反射系数。