Rainfall Estimation Based on the Intensity of the Received Signal in a LTE/4G Mobile Terminal by Using a Probabilistic Neural Network
Rainfall Estimation Based on the Intensity of the Received Signal in a LTE/4G Mobile Terminal by Using a Probabilistic Neural Network
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DOI：
10.1109/access.2018.2839699
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发表时间：
2018-01-01
期刊：
影响因子：
3.9
通讯作者：
Scaglione, Francesco
中科院分区：
文献类型：
--
作者：
Beritelli, Francesco;Capizzi, Giacomo;Scaglione, Francesco
基于降雨对电磁波影响的降雨量估算是一种新颖的方法，在过去几年中取得了显着的进步。过去对此主题进行的许多研究仅考虑频率大于 10 GHz 的电磁波，因为降雨对电磁波衰减的影响在较低频率下会减小。在过去的几年中，一些作者已经证明，即使在下雨的情况下，移动通信移动终端的全球系统接收到的信号也可能存在不可忽略的衰减。在本文中，我们提出了一种基于概率神经网络的新分类方法，以获得四种降雨强度（无雨、弱雨、中雨和大雨）之间的准确分类。创新的降雨分类方法基于 4G/LTE 的三个接收信号电平 (RSL) 局部特征：瞬时 RSL、平均 RSL 值及其使用滑动窗口计算的方差。该方法表现出良好的性能，总体正确分类率为 96.7%。文献中几乎所有关于该主题的论文都集中于频率大于 10 GHz 的电磁波，根据雨衰模型，其中降雨的影响更为相关。然而，只有 4G/LTE 信号具有如此广泛的地理覆盖范围，因此所提出的分类方法可以在创建具有更高空间分辨率的降雨图方面提供显着改进。
Rainfall estimation based on the impact of rain on electromagnetic waves is a novel methodology that has had notable advancements during the last few years. Many studies conducted on this topic in the past considered only the electromagnetic waves with frequencies greater than 10 GHz since the rainfall impact on the electromagnetic wave attenuation is reduced at lower frequencies. Over the last few years, some authors have demonstrated that there can be a non-negligible attenuation even on the signals received on a global system for mobile communications mobile terminal in presence of rain. In this paper, we propose a new classification method based on a probabilistic neural network to obtain an accurate classification between four rainfall intensities (no rain, weak rain, moderate rain, and heavy rain). The innovative rainfall classification method is based on three received signal level (RSL) local features of the 4G/LTE: the instantaneous RSL, the average RSL value, and its variance calculated by using a sliding window. The proposed method exhibits good performance, obtaining an overall correct classification rate of 96.7%. Almost all papers on this topic present in the literature focus on electromagnetic waves with frequencies greater than 10 GHz, in which the rain impact is more relevant, according to the rain attenuation model. However, only the 4G/LTE signal has such widespread geographic coverage, so the proposed classification method can provide noticeable improvements in the creation of rainfall maps with higher spatial resolution.