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视距郊区环境下车路通信大规模无线信道的平稳时间

On the Stationarity Time of a Vehicle-to-Infrastructure Massive Radio Channel in a Line-of-Sight Suburban Environment.

作者信息

Dahmouni Nor El Islam, Laly Pierre, Yusuf Marwan, Delbarre Gauthier, Liénard Martine, Simon Eric P, Gaillot Davy P

机构信息

Univ. Lille, CNRS, UMR 8520-IEMN, F-59000 Lille, France.

Department of Information Technology IMEC-WAVES, Ghent University, 9052 Gent, Belgium.

出版信息

Sensors (Basel). 2022 Nov 2;22(21):8420. doi: 10.3390/s22218420.

DOI:10.3390/s22218420
PMID:36366118
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9656889/
Abstract

Massive multiple-input multiple-output (mMIMO) communication systems are a pillar technology for 5G. However, the wireless radio channel models relying on the assumption of wide-sense stationary uncorrelated scattering (WSSUS) may not always be valid for dynamic scenarios. Nonetheless, an analysis of the stationarity time that validates this hypothesis for mMIMO vehicular channels as well as a clear relationship with the scattering properties is missing in the literature. Here, time-varying single-user mMIMO radio channels were measured in a suburban environment at the 5.89 GHz vehicular band with a strong Line-of-Sight (LOS) to study the non-WSSUS and large scale characteristics of the vehicle-to-infrastructure (V2I) link. The generalized local scattering function (GLSF), computed from the sampled channels, was used to derive (1) the spatial distribution of the stationarity time using the channel correlation function (CCF) and empirical collinearity methods and (2) the root mean square delay/angular spread and coherence time/bandwidth values from the projected power delay profile () and Doppler power spectra (). The results highlight the high degree of correlation between the spatial distribution of the stationarity time and the scattering properties along the measurement route.

摘要

大规模多输入多输出(mMIMO)通信系统是5G的一项支柱技术。然而,依赖广义平稳不相关散射(WSSUS)假设的无线信道模型在动态场景中可能并不总是有效。尽管如此,文献中缺少对mMIMO车载信道验证该假设的平稳时间的分析以及与散射特性的明确关系。在此,在5.89GHz车载频段的郊区环境中,在具有强视距(LOS)的情况下测量了时变单用户mMIMO无线信道,以研究车对基础设施(V2I)链路的非WSSUS和大尺度特性。从采样信道计算得到的广义局部散射函数(GLSF)用于(1)使用信道相关函数(CCF)和经验共线性方法推导平稳时间的空间分布,以及(2)从投影功率延迟分布()和多普勒功率谱()中得出均方根延迟/角扩展以及相干时间/带宽值。结果突出了平稳时间的空间分布与沿测量路线的散射特性之间的高度相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/930dc562d664/sensors-22-08420-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/8f1a3c64a5e3/sensors-22-08420-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/5f9d7c361750/sensors-22-08420-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/2685b7413712/sensors-22-08420-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/9a5307017424/sensors-22-08420-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/11b96d557639/sensors-22-08420-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/8ab53616d53e/sensors-22-08420-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/871c86f06c44/sensors-22-08420-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/ff0cdaf81c30/sensors-22-08420-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/d2b6d48d24b7/sensors-22-08420-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/f80279089500/sensors-22-08420-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/af7d0cb14237/sensors-22-08420-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/930dc562d664/sensors-22-08420-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/8f1a3c64a5e3/sensors-22-08420-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/5f9d7c361750/sensors-22-08420-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/2685b7413712/sensors-22-08420-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/9a5307017424/sensors-22-08420-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/11b96d557639/sensors-22-08420-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/8ab53616d53e/sensors-22-08420-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/871c86f06c44/sensors-22-08420-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/ff0cdaf81c30/sensors-22-08420-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/d2b6d48d24b7/sensors-22-08420-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/f80279089500/sensors-22-08420-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/af7d0cb14237/sensors-22-08420-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/743a/9656889/930dc562d664/sensors-22-08420-g012.jpg

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