Near-field wideband beam training for ELAA with uniform circular array

IF 7.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Science China Information Sciences Pub Date : 2024-05-24 DOI:10.1007/s11432-023-3970-7
Yuhao Chen, Linglong Dai
{"title":"Near-field wideband beam training for ELAA with uniform circular array","authors":"Yuhao Chen, Linglong Dai","doi":"10.1007/s11432-023-3970-7","DOIUrl":null,"url":null,"abstract":"<p>Extremely large-scale antenna array (ELAA) at millimeter wave (mmWave) and Terahertz (THz) band has been considered a key technology for combating high attenuation in high-frequency bands in future 6G communications. Uniform circular arrays (UCAs) have attracted much attention because of their ability to provide flat beamforming gain at all angles. To realize efficient beamforming, beam training is widely used to acquire channel state information. However, with a large antenna number, the beam training overhead in ELAA systems becomes overwhelming. Moreover, with a large bandwidth, the beam defocus effect severely degrades beam training accuracy. To address these issues, this paper proposes a frequency-dependent focusing (FDF)-based beam training scheme to realize effective beam training in near-field wideband ELAA systems with UCA. Specifically, we first analyze the FDF property of UCA, where signals at different subcarriers can simultaneously focus on different distances. Then, by exploiting the FDF property to search different distances using different subcarriers simultaneously, we design a hierarchical codebook and propose an FDF-based beam training scheme. To reveal the effectiveness of the proposed scheme, we compare its necessary beam training overhead with that of existing schemes. Finally, the simulation results demonstrate that the proposed scheme can achieve accurate beam training in near-field wideband UCA systems with a low beam training overhead.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":null,"pages":null},"PeriodicalIF":7.3000,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science China Information Sciences","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11432-023-3970-7","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Extremely large-scale antenna array (ELAA) at millimeter wave (mmWave) and Terahertz (THz) band has been considered a key technology for combating high attenuation in high-frequency bands in future 6G communications. Uniform circular arrays (UCAs) have attracted much attention because of their ability to provide flat beamforming gain at all angles. To realize efficient beamforming, beam training is widely used to acquire channel state information. However, with a large antenna number, the beam training overhead in ELAA systems becomes overwhelming. Moreover, with a large bandwidth, the beam defocus effect severely degrades beam training accuracy. To address these issues, this paper proposes a frequency-dependent focusing (FDF)-based beam training scheme to realize effective beam training in near-field wideband ELAA systems with UCA. Specifically, we first analyze the FDF property of UCA, where signals at different subcarriers can simultaneously focus on different distances. Then, by exploiting the FDF property to search different distances using different subcarriers simultaneously, we design a hierarchical codebook and propose an FDF-based beam training scheme. To reveal the effectiveness of the proposed scheme, we compare its necessary beam training overhead with that of existing schemes. Finally, the simulation results demonstrate that the proposed scheme can achieve accurate beam training in near-field wideband UCA systems with a low beam training overhead.

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
采用均匀圆形阵列的近场宽带波束训练 ELAA
毫米波(mmWave)和太赫兹(THz)频段的超大规模天线阵列(ELAA)被认为是应对未来 6G 通信高频段高衰减的关键技术。均匀圆形阵列(UCA)因其能够在所有角度提供平坦的波束成形增益而备受关注。为实现高效波束成形,波束训练被广泛用于获取信道状态信息。然而,当天线数量较多时,ELAA 系统的波束训练开销会变得非常大。此外,在带宽较大的情况下,波束散焦效应会严重降低波束训练的精度。为了解决这些问题,本文提出了一种基于频率相关聚焦(FDF)的波束训练方案,以在具有 UCA 的近场宽带 ELAA 系统中实现有效的波束训练。具体来说,我们首先分析了 UCA 的 FDF 特性,即不同子载波上的信号可同时聚焦在不同距离上。然后,通过利用 FDF 特性同时使用不同子载波搜索不同距离,我们设计了一个分层码本,并提出了基于 FDF 的波束训练方案。为了揭示所提方案的有效性,我们将其所需的波束训练开销与现有方案进行了比较。最后,仿真结果表明,所提方案能在近场宽带 UCA 系统中实现精确波束训练,且波束训练开销较低。
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
Science China Information Sciences
Science China Information Sciences COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
12.60
自引率
5.70%
发文量
224
审稿时长
8.3 months
期刊介绍: Science China Information Sciences is a dedicated journal that showcases high-quality, original research across various domains of information sciences. It encompasses Computer Science & Technologies, Control Science & Engineering, Information & Communication Engineering, Microelectronics & Solid-State Electronics, and Quantum Information, providing a platform for the dissemination of significant contributions in these fields.
期刊最新文献
Weighted sum power maximization for STAR-RIS-aided SWIPT systems with nonlinear energy harvesting TSCompiler: efficient compilation framework for dynamic-shape models NeurDB: an AI-powered autonomous data system State and parameter identification of linearized water wave equation via adjoint method An STP look at logical blocking of finite state machines: formulation, detection, and search
×
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