Suppr超能文献

地面链路降雨衰减预测模型综述——当前研究挑战和最新技术。

A Survey of Rain Attenuation Prediction Models for Terrestrial Links-Current Research Challenges and State-of-the-Art.

机构信息

Department of Information and Communication Engineering, Chosun University, Gwangju 61452, Korea.

Department of Electronics and Telecommunication Engineering, International Islamic University Chittagong, Chittagong 4318, Bangladesh.

出版信息

Sensors (Basel). 2021 Feb 9;21(4):1207. doi: 10.3390/s21041207.

Abstract

Millimeter-wave (30-300 GHz) frequency is a promising candidate for 5G and beyond wireless networks, but atmospheric elements limit radio links at this frequency band. Rainfall is the significant atmospheric element that causes attenuation in the propagated wave, which needs to estimate for the proper operation of fade mitigation technique (FMT). Many models have been proposed in the literature to estimate rain attenuation. Various models have a distinct set of input parameters along with separate estimation mechanisms. This survey has garnered multiple techniques that can generate input dataset for the rain attenuation models. This study extensively investigates the existing terrestrial rain attenuation models. There is no survey of terrestrial rain mitigation models to the best of our knowledge. In this article, the requirements of this survey are first discussed, with various dataset developing techniques. The terrestrial links models are classified, and subsequently, qualitative and quantitative analyses among these terrestrial rain attenuation models are tabulated. Also, a set of error performance evaluation techniques is introduced. Moreover, there is a discussion of open research problems and challenges, especially the exigency for developing a rain attenuation model for the short-ranged link in the -band for 5G and beyond networks.

摘要

毫米波(30-300GHz)频率是 5G 及未来无线网络的有前途的候选者,但大气元素限制了该频段的无线电链路。降雨是导致传播波衰减的重要大气元素,需要对其进行估计,以便正确运行衰落缓解技术(FMT)。文献中已经提出了许多模型来估计降雨衰减。各种模型具有一组独特的输入参数以及单独的估计机制。本调查收集了多种可生成降雨衰减模型输入数据集的技术。本研究广泛调查了现有的地面降雨衰减模型。据我们所知,目前还没有对地面降雨缓解模型的调查。在本文中,首先讨论了这项调查的要求,并讨论了各种数据集开发技术。对地面链路模型进行了分类,然后对这些地面降雨衰减模型进行了定性和定量分析。还介绍了一组错误性能评估技术。此外,还讨论了开放的研究问题和挑战,特别是对于为 5G 及未来网络的短程链路开发 - 波段的降雨衰减模型的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be43/7915915/b6f477a9bf13/sensors-21-01207-g001.jpg

相似文献

2
Opportunistic Rain Rate Estimation from Measurements of Satellite Downlink Attenuation: A Survey.
Sensors (Basel). 2021 Aug 31;21(17):5872. doi: 10.3390/s21175872.
3
Millimeter Wave Attenuation Due to Wind and Heavy Rain in a Tropical Region.
Sensors (Basel). 2023 Feb 24;23(5):2532. doi: 10.3390/s23052532.
4
Tropospheric attenuation prediction for future millimeter wave terrestrial systems: Estimating statistics and extremes.
Int J Commun Syst. 2022 Sep 10;35(13):e5240. doi: 10.1002/dac.5240. Epub 2022 May 30.
5
Research on Rainfall Monitoring Based on E-Band Millimeter Wave Link in East China.
Sensors (Basel). 2021 Mar 1;21(5):1670. doi: 10.3390/s21051670.
6
Rain rate modeling of 1-min from various integration times in South Korea.
Springerplus. 2016 Apr 12;5:433. doi: 10.1186/s40064-016-2062-3. eCollection 2016.
7
Variability and trends in rain height retrieved from GPM and implications on rain-induced attenuation over Nigeria.
Heliyon. 2021 Oct 1;7(10):e08108. doi: 10.1016/j.heliyon.2021.e08108. eCollection 2021 Oct.
10

引用本文的文献

本文引用的文献

1
Application of the deep learning for the prediction of rainfall in Southern Taiwan.
Sci Rep. 2019 Sep 4;9(1):12774. doi: 10.1038/s41598-019-49242-6.
2
State-of-the-art in artificial neural network applications: A survey.
Heliyon. 2018 Nov 23;4(11):e00938. doi: 10.1016/j.heliyon.2018.e00938. eCollection 2018 Nov.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验