Suppr超能文献

面向 6G 的基于智能反射面的无线通信的机器学习:综述。

Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review.

机构信息

Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea.

Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Korea.

出版信息

Sensors (Basel). 2022 Jul 20;22(14):5405. doi: 10.3390/s22145405.

Abstract

An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. In addition, machine learning (ML) techniques are now widely adopted in wireless communication as the computation power of devices has increased. As it is an emerging topic, we provide a comprehensive overview of the state-of-the-art on ML, especially on deep learning (DL)-based IRS-enhanced communication. We focus on their operating principles, channel estimation (CE), and the applications of machine learning to IRS-enhanced wireless networks. In addition, we systematically survey existing designs for IRS-enhanced wireless networks. Furthermore, we identify major issues and research opportunities associated with the integration of IRS and other emerging technologies for applications to next-generation wireless communication.

摘要

智能反射面(IRS)是一种可编程设备,可通过改变其表面的电和磁特性来控制电磁波的传播。因此,IRS 被认为是第六代(6G)通信网络的一项智能技术。此外,随着设备计算能力的提高,机器学习(ML)技术现在已广泛应用于无线通信领域。由于这是一个新兴的主题,我们提供了关于 ML 的最新技术的全面概述,特别是基于深度学习(DL)的 IRS 增强型通信。我们重点介绍了它们的工作原理、信道估计(CE)以及机器学习在 IRS 增强型无线网络中的应用。此外,我们系统地调查了现有的 IRS 增强型无线网络设计。此外,我们确定了与 IRS 集成以及将其他新兴技术应用于下一代无线通信相关的主要问题和研究机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e082/9316605/2664510831d9/sensors-22-05405-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验