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arXiv 2401.17014cs.ITeess.SPmath.IT
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面向 ELAAs 的近场衰落信道建模:从通信到 ISAC

Near-Field Fading Channel Modeling for ELAAs: From Communication to ISAC

Jiuyu Liu, Yi Ma, Ahmed Elzanaty, Rahim Tafazolli

AI总结:

本文提出面向通信与 ISAC 的 ELAA 近场衰落信道生成框架及 3D URA 信道模型,可刻画 LoS/NLoS 混合、球面波、非平稳阴影衰落和感知对象影响,并基于 3GPP 参数支持标准化。

摘要:

极大孔径阵列(ELAA)预计将成为 6G 中未来多输入多输出(MIMO)系统的关键特征。近场(NF)衰落信道模型对于可靠的链路级仿真和 ELAA 系统设计至关重要。本文提出一个框架,旨在为通信以及通感一体化(ISAC)应用生成 NF 衰落信道。该框架允许视距(LoS)和非视距(NLoS)链路混合存在,同时考虑球面波模型和空间非平稳阴影衰落。基于该框架,我们针对部署均匀矩形阵列(URA)的 ELAA 系统提出了一种三维(3D)衰落信道模型。该模型能够捕捉 ISAC 应用中感知对象带来的影响。此外,框架涉及的所有参数均基于第三代合作伙伴计划(3GPP)文件中的规范或测量结果。因此,所提出的框架和信道模型有潜力在多个方面为标准作出贡献,包括 ISAC、超大(XL-)MIMO 以及可重构智能表面(RIS)辅助的 MIMO 系统。最后,本文给出了 ELAA 的未来方向,不仅包括 NF 信道建模,还包括下一代收发器设计。

英文摘要:

Extremely large aperture array (ELAA) is anticipated to serve as a pivotal feature of future multiple-input multiple-output (MIMO) systems in 6G. Near-field (NF) fading channel models are essential for reliable link-level simulation and ELAA system design. In this article, we propose a framework designed to generate NF fading channels for both communication and integrated sensing and communication (ISAC) applications. The framework allows a mixed of line of sight (LoS) and non-LoS (NLoS) links. It also considers spherical wave model and spatially non-stationary shadow fading. Based on this framework, we propose a three-dimensional (3D) fading channel model for ELAA systems deployed with a uniform rectangular array (URA). It can capture the impact of sensing object for ISAC applications. Moreover, all parameters involved in the framework are based on specifications or measurements from the 3rd Generation Partnership Project (3GPP) documents. Therefore, the proposed framework and channel model have the potential to contribute to the standard in various aspects, including ISAC, extra-large (XL-) MIMO, and reconfigurable intelligent surface (RIS) aided MIMO systems. Finally, future directions for ELAA are presented, including not only NF channel modeling but also the design of next-generation transceivers.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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