Unscented Kalman Filter-based Beam Tracking in NR MIMO System using Hybrid Beamforming

Yuna Sim, S. Sin, Ji-Haeng Cho, Kyunam Kim, Sangmi Moon, I. Hwang
{"title":"Unscented Kalman Filter-based Beam Tracking in NR MIMO System using Hybrid Beamforming","authors":"Yuna Sim, S. Sin, Ji-Haeng Cho, Kyunam Kim, Sangmi Moon, I. Hwang","doi":"10.1109/ICAIIC57133.2023.10067030","DOIUrl":null,"url":null,"abstract":"Unmanned aerial vehicles (UAVs) and millimeter wave frequencies play a key role in supporting 5G wireless communication systems. They expand the area of wireless communication by increasing the data capacity in communication systems and supporting high data rates. However, short wavelengths, due to their high millimeter wave frequencies cause problems arising from signal attenuation and path loss. To address these limitations, research centered on high directional beamforming technology continues to gather interest. Furthermore, due to the mobility of UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. In this study, we propose a beam tracking method based on the unscented Kalman filter using hybrid beamforming. By expanding analog beamforming to hybrid beamforming, our proposed algorithm can be used even in multi-user and multi-stream environments, increasing the data capacity, and, thus increasing utilization in new radio multiple-input multiple-output orthogonal frequency diversity multiplexing systems.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIIC57133.2023.10067030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Unmanned aerial vehicles (UAVs) and millimeter wave frequencies play a key role in supporting 5G wireless communication systems. They expand the area of wireless communication by increasing the data capacity in communication systems and supporting high data rates. However, short wavelengths, due to their high millimeter wave frequencies cause problems arising from signal attenuation and path loss. To address these limitations, research centered on high directional beamforming technology continues to gather interest. Furthermore, due to the mobility of UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. In this study, we propose a beam tracking method based on the unscented Kalman filter using hybrid beamforming. By expanding analog beamforming to hybrid beamforming, our proposed algorithm can be used even in multi-user and multi-stream environments, increasing the data capacity, and, thus increasing utilization in new radio multiple-input multiple-output orthogonal frequency diversity multiplexing systems.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于无气味卡尔曼滤波的混合波束形成NR MIMO系统波束跟踪
无人机(uav)和毫米波频率在支持5G无线通信系统中发挥着关键作用。它们通过增加通信系统中的数据容量和支持高数据速率来扩展无线通信的领域。然而,短波长由于其高毫米波频率而引起信号衰减和路径损耗的问题。为了解决这些限制,以高定向波束形成技术为中心的研究不断引起人们的兴趣。此外,由于无人机的机动性,为了获得完整的波束形成增益,必须准确跟踪波束角。在本研究中,我们提出了一种基于混合波束形成的无气味卡尔曼滤波波束跟踪方法。通过将模拟波束形成扩展到混合波束形成,我们提出的算法甚至可以在多用户和多流环境中使用,增加了数据容量,从而提高了新的无线电多输入多输出正交频分集复用系统的利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Development of AI Educational Datasets Library Using Synthetic Dataset Generation Method Channel Access Control Instead of Random Backoff Algorithm Illegal 3D Content Distribution Tracking System based on DNN Forensic Watermarking Deep Learning-based Spectral Efficiency Maximization in Massive MIMO-NOMA Systems with STAR-RIS Data Pipeline Design for Dangerous Driving Behavior Detection System
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1