Comparative Study on a 60 GHz Path Loss Channel Modeling in a Mine Environment Using Neural Networks

N. Zaarour, S. Affes, N. Kandil, N. Hakem
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引用次数: 12

Abstract

A precise and accurate channel model is essential in conceiving and designing wireless telecommunication systems. However, modeling the channel in a confined and harsh environment such as an underground mine is more complicated and challenging. In this paper, we present an experimental study on modeling a 60 GHz path loss fading based on experimental measurements made in an underground former gold mine. To address the accuracy of artificial neural networks (ANN) in modeling problems, an approach based on two well- known ANN, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) is considered, and a comparison between them in modeling the path loss attenuation is evaluated.
基于神经网络的矿井环境60ghz路径损耗信道建模比较研究
在构思和设计无线通信系统时,精确的信道模型是必不可少的。然而,在一个狭窄和恶劣的环境中,如地下矿山,建立通道模型是更加复杂和具有挑战性的。本文基于某地下原金矿的实验测量,对60 GHz路径损耗衰落建模进行了实验研究。为了解决人工神经网络(ANN)在建模问题中的准确性问题,考虑了基于两种著名的神经网络——多层感知器(MLP)和径向基函数(RBF)的方法,并比较了它们在建模路径损耗衰减方面的效果。
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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