In this paper, we consider the application of intelligent reflecting surface (IRS) in unmanned aerial vehicle (UAV)-based orthogonal frequency division multiple access (OFDMA) communication systems, which exploits both the significant beamforming gain brought by the IRS and the high mobility of UAV for improving the system sum-rate. The joint design of UAV's trajectory, IRS scheduling, and communication resource allocation for the proposed system is formulated as a non-convex optimization problem to maximize the system sum-rate while taking into account the heterogeneous quality-of-service (QoS) requirement of each user. The existence of an IRS introduces both frequency-selectivity and spatial-selectivity in the fading of the composite channel from the UAV to ground users. To facilitate the design, we first derive the expression of the composite channels and propose a parametric approximation approach to establish an upper and a lower bound for the formulated problem. An alternating optimization algorithm is devised to handle the lower bound optimization problem and its performance is compared with the benchmark performance achieved by solving the upper bound problem. Simulation results unveil the small gap between the developed bounds and the promising sum-rate gain achieved by the deployment of an IRS in UAV-based communication systems.

中文翻译：

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IRS 辅助无人机 OFDMA 通信系统的和速率最大化

在本文中，我们考虑了智能反射面 (IRS) 在基于无人机 (UAV) 的正交频分多址 (OFDMA) 通信系统中的应用，该系统利用了 IRS 带来的显着波束成形增益和高移动性提高系统总速率的无人机。所提出系统的无人机轨迹、IRS 调度和通信资源分配的联合设计被制定为非凸优化问题，以最大化系统总速率，同时考虑到异构服务质量 (QoS) 要求每个用户。IRS 的存在在从无人机到地面用户的复合信道衰落中引入了频率选择性和空间选择性。为了方便设计，我们首先推导出复合通道的表达式，并提出一种参数近似方法来为公式化问题建立上限和下限。设计了一种交替优化算法来处理下界优化问题，并将其性能与通过解决上界问题获得的基准性能进行比较。仿真结果揭示了开发边界与在基于无人机的通信系统中部署 IRS 所实现的有希望的总速率增益之间的小差距。设计了一种交替优化算法来处理下界优化问题，并将其性能与通过解决上界问题获得的基准性能进行比较。仿真结果揭示了开发边界与在基于无人机的通信系统中部署 IRS 所实现的有希望的总速率增益之间的小差距。设计了一种交替优化算法来处理下界优化问题，并将其性能与通过解决上界问题获得的基准性能进行比较。仿真结果揭示了开发边界与在基于无人机的通信系统中部署 IRS 所实现的有希望的总速率增益之间的小差距。