This paper proposes a solution for energy-efficient communication in reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV) networks. The limited battery life of UAVs is a major concern for their sustainable operation, and RIS has emerged as a promising solution to reducing the energy consumption of communication systems. The paper formulates the problem of maximizing the energy efficiency of the network as a mixed integer non-linear program, in which UAV placement, UAV beamforming, On-Off strategy of RIS elements, and phase shift of RIS elements are optimized. The proposed solution utilizes the block coordinate descent approach and a combination of continuous and binary genetic algorithms. Moreover, for optimizing the UAV placement, Adam optimizer is used. The simulation results show that the proposed solution outperforms the existing literature. Specifically, we compared the proposed method with the successive convex approximation (SCA) approach for optimizing the phase shift of RIS elements.

翻译：本文提出了一种用于可重构智能表面(RIS)辅助无人机(UAV)网络的节能通信解决方案。无人机电池寿命有限是制约其可持续运行的主要问题，而RIS作为一种有前景的解决方案，能够降低通信系统的能耗。本文将网络能效最大化问题建模为混合整数非线性规划，并优化了无人机部署位置、无人机波束赋形、RIS单元开关策略以及RIS单元相位偏移。所提方案采用块坐标下降法，结合连续型与二进制遗传算法进行求解。此外，在优化无人机部署位置时使用了Adam优化器。仿真结果表明，所提方案优于现有文献方法。具体而言，我们将所提方法与用于优化RIS单元相位偏移的逐次凸近似(SCA)方法进行了对比。