论文标题
IRS辅助无人机的总和最大化DMA通信系统
Sum-Rate Maximization for IRS-Assisted UAV OFDMA Communication Systems
论文作者
论文摘要
在本文中,我们考虑了智能反射表面(IRS)在无人机(UAV)基于基于基于的正交频部的多个访问(OFDMA)通信系统中的应用,这利用了IRS带来的显着波束成型增益,以及无人机的高迁移率,用于改善系统总成果。所提出的系统的无人机轨迹,IRS计划和通信资源分配的联合设计被作为非凸优化问题提出,以最大程度地提高系统总和率,同时考虑到每个用户的异质服务质量(QOS)要求。 IRS的存在引入了频率选择性和空间选择性,在从无人机到地面用户的复合通道褪色中。为了促进设计,我们首先得出了复合通道的表达,并提出了一种参数近似方法,以建立公式问题的上限和下限。设计了交替的优化算法来处理下界优化问题,并将其性能与通过解决上限问题实现的基准性能进行比较。仿真结果揭示了开发界限与通过基于无人机的通信系统中的IRS部署实现的有希望的总和收益之间的较小差距。
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.