Near-field channel estimation for extremely large-scale Terahertz communications

IF 7.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Songjie Yang, Yizhou Peng, Wanting Lyu, Ya Li, Hongjun He, Zhongpei Zhang, Chau Yuen
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Abstract

Future Terahertz communications exhibit significant potential in accommodating ultra-high-rate services. Employing extremely large-scale array antennas is a key approach to realize this potential, as they can harness substantial beamforming gains to overcome the severe path loss and leverage the electromagnetic advantages in the near field. This paper proposes novel estimation methods designed to enhance efficiency in Terahertz widely-spaced multi-subarray (WSMS) systems. Initially, we introduce three sparse channel representation methods: polar-domain representation (PD-R), multi-angular-domain representation (MAD-R), and two-dimensional polar-angular-domain representation (2D-PAD-R). Each method is meticulously developed for near-field WSMS channels, capitalizing on their sparsity characteristics. Building on this, we propose four estimation frameworks using the sparse recovery theory: polar-domain estimation (PD-E), multi-angular-domain estimation (MAD-E), two-stage polar-angular-domain estimation (TS-PAD-E), and two-dimensional polar-angular-domain estimation (2D-PAD-E). Particularly, 2D-PAD-E, integrating a 2D dictionary process, and TS-PAD-E, with its sequential approach to angle and distance estimation, stand out as particularly effective for near-field angle-distance estimation, enabling decoupled calculation of these parameters. Overall, these frameworks provide versatile and efficient solutions for WSMS channel estimation, balancing low complexity with high-performance outcomes. Additionally, they represent a fresh perspective on near-field signal processing.

超大规模太赫兹通信的近场信道估计
未来的太赫兹通信在提供超高速服务方面具有巨大潜力。采用超大规模阵列天线是实现这一潜力的关键方法,因为它们可以利用大量波束成形增益来克服严重的路径损耗,并充分利用近场电磁优势。本文提出了新颖的估计方法,旨在提高太赫兹宽间隔多子阵列(WSMS)系统的效率。首先,我们介绍了三种稀疏信道表示方法:极域表示法(PD-R)、多角域表示法(MAD-R)和二维极角域表示法(2D-PAD-R)。每种方法都是针对近场 WSMS 信道精心开发的,充分利用了信道的稀疏性特点。在此基础上,我们利用稀疏恢复理论提出了四种估计框架:极域估计(PD-E)、多角域估计(MAD-E)、两阶段极角域估计(TS-PAD-E)和二维极角域估计(2D-PAD-E)。其中,2D-PAD-E 集成了 2D 字典过程,TS-PAD-E 则采用了角度和距离估算的顺序方法,对近场角度-距离估算特别有效,可实现这些参数的解耦计算。总之,这些框架为 WSMS 信道估计提供了多功能、高效的解决方案,在低复杂度和高性能结果之间取得了平衡。此外,它们还代表了近场信号处理的全新视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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.
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