Intelligent reflecting surface (IRS) is an emerging technology to enhance the spectral and energy efficiency of wireless communications cost-effectively. This letter considers a new multi-IRS aided wireless network where a cascaded line-of-sight (LoS) link is established between the base station (BS) and a remote user by leveraging the multi-hop signal reflection of selected IRSs. As compared to the conventional single-/double-hop IRS system, multi-hop IRS system provides more pronounced path diversity and cooperative passive beamforming gains, especially in the environment with dense obstacles. However, a more challenging joint active/passive beamforming and multi-hop beam routing problem also arises for maximizing the end-to-end channel gain. Furthermore, the number of IRS-associated channel coefficients increases drastically with the number of IRS hops. To tackle the above issues, in this letter we propose a new and efficient beam training based solution by considering the use of practical codebook-based BS/IRS active/passive beamforming without the need of explicit channel estimation. Instead of exhaustively or sequentially searching over all combinations of active and passive beam patterns for each beam route, a distributed beam training scheme is proposed to reduce the complexity, by exploiting the (nearly) time-invariant BS-IRS and inter-IRS channels and the cooperative training among the BS and IRSs' controllers. Simulation results show that our proposed design achieves the end-to-end channel gain close to that of the sequential beam search, but at a much lower training overhead and complexity.


翻译:智能反射表面(IRS)是提高无线通信光谱和能源效率的一种新兴技术,具有成本效益。本信考虑了一个新的多IRS辅助型无线网络,基础站和一个远程用户通过利用选定的IRS多光点信号反射,在其中建立了连锁线-视距(LOS)链接。与传统的单/双跳IRS系统相比,多点IRS系统提供了更明显的路径多样性和合作性被动波束增益,特别是在有密集障碍的环境中。然而,一个更具挑战性的多点/被动波形和多点波波形无线无线网络,使基地台站站和远程用户之间建立了连锁-视线(LOS)链接。此外,与IRS相关频道的系数随着IRS跳线数的增加而急剧增加。为了解决上述问题,我们在信中提出一个新的高效培训解决方案,即考虑使用实用的基于代码集的BS/IRS主动/被动/被动波形组合,而无需明确对BRS系统进行直线-直线-直线波段和多波形路路段估算,而是在BS系统上进行主动和连续搜索中进行快速搜索,从而在BS系统上进行最精确的组合中进行最精确的搜索和连续搜索式搜索式搜索,从而在BS系统图图式搜索和连续地展示,从而在BS系统图图图图图图图图中进行最精确地研究,在BS系统上进行最精确和连续地研究中进行最精细图图图图图图图式搜索图图图图图式搜索式研究。在BS图式的每个图式研究。

0
下载
关闭预览

相关内容

【图与几何深度学习】Graph and geometric deep learning,49页ppt
Linux导论,Introduction to Linux,96页ppt
专知会员服务
78+阅读 · 2020年7月26日
Python分布式计算,171页pdf,Distributed Computing with Python
专知会员服务
107+阅读 · 2020年5月3日
[综述]深度学习下的场景文本检测与识别
专知会员服务
77+阅读 · 2019年10月10日
已删除
将门创投
5+阅读 · 2018年1月24日
A Survey on Edge Intelligence
Arxiv
51+阅读 · 2020年3月26日
VIP会员
相关资讯
已删除
将门创投
5+阅读 · 2018年1月24日
Top
微信扫码咨询专知VIP会员