We consider unmanned aerial vehicle (UAV)-enabled wireless systems where downlink communications between a multi-antenna UAV and multiple users are assisted by a hybrid active-passive reconfigurable intelligent surface (RIS). We aim at a fairness design of two typical UAV-enabled networks, namely the static-UAV network where the UAV is deployed at a fixed location to serve all users at the same time, and the mobile-UAV network which employs the time division multiple access protocol. In both networks, our goal is to maximize the minimum rate among users through jointly optimizing the UAV's location/trajectory, transmit beamformer, and RIS coefficients. The resulting problems are highly nonconvex due to a strong coupling between the involved variables. We develop efficient algorithms based on block coordinate ascend and successive convex approximation to effectively solve these problems in an iterative manner. In particular, in the optimization of the mobile-UAV network, closed-form solutions to the transmit beamformer and RIS passive coefficients are derived. Numerical results show that a hybrid RIS equipped with only 4 active elements and a power budget of 0 dBm offers an improvement of 38%-63% in minimum rate, while that achieved by a passive RIS is only about 15%, with the same total number of elements.

翻译：我们研究了由混合主动-被动可重构智能表面（RIS）辅助的多天线无人机与多用户下行链路通信的无人机无线系统。我们针对两种典型的无人机使能网络进行公平性设计，即静态无人机网络（无人机部署于固定位置同时服务所有用户）和移动无人机网络（采用时分多址协议）。在这两种网络中，我们通过联合优化无人机的位置/轨迹、发射波束成形器和RIS系数，旨在最大化用户间的最小速率。由于变量之间存在强耦合，所得到的优化问题高度非凸。我们基于块坐标上升法和逐次凸近似开发了高效算法，以迭代方式有效求解这些问题。特别地，在移动无人机网络的优化中，我们推导出了发射波束成形器和RIS无源系数的闭式解。数值结果表明，在元件总数相同的情况下，配备仅4个有源元件且功率预算为0 dBm的混合RIS可将最小速率提升38%-63%，而纯无源RIS的该项提升仅为约15%。