论文标题
6G中的智能反射表面部署：一项全面的调查
Intelligent Reflective Surface Deployment in 6G: A Comprehensive Survey
论文作者
论文摘要
智能反射表面（IRSS）被认为是一种有前途的技术，可以巧妙地重新配置无线环境以增强未来无线网络的性能。但是，由于高度动态和移动的无人机（UAV）使无线环境能够实现更高的容量，IRSS的部署仍然面临挑战。本文阐明了未来的地面和非事物网络中IRS的不同部署策略。具体而言，在本文中，我们介绍了IRS范式基础的关键理论概念，并讨论了与6G网络中IRS部署有关的设计方面。我们还探索了基于优化的IRS部署技术，以提高陆地和空中IRS的系统性能。此外，我们调查了从部署方面的无模型增强学习（RL）技术，以应对在复杂和移动IRS辅助无人机无线系统中实现更高容量的挑战。最后，我们重点介绍了IRS部署方面的挑战和未来的研究方向，以改善未来6G网络的系统性能。
Intelligent reflecting surfaces (IRSs) are considered a promising technology that can smartly reconfigure the wireless environment to enhance the performance of future wireless networks. However, the deployment of IRSs still faces challenges due to highly dynamic and mobile unmanned aerial vehicle (UAV) enabled wireless environments to achieve higher capacity. This paper sheds light on the different deployment strategies for IRSs in future terrestrial and non-terrestrial networks. Specifically, in this paper, we introduce key theoretical concepts underlying the IRS paradigm and discuss the design aspects related to the deployment of IRSs in 6G networks. We also explore optimization-based IRS deployment techniques to improve system performance in terrestrial and aerial IRSs. Furthermore, we survey model-free reinforcement learning (RL) techniques from the deployment aspect to address the challenges of achieving higher capacity in complex and mobile IRS-assisted UAV wireless systems. Finally, we highlight challenges and future research directions from the deployment aspect of IRSs for improving system performance for the future 6G network.
