Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings

Symmetry-based channel digital twin is a great technology which can reproduce the communication channel of real scenes for performance evaluation of the wireless sensor network (WSN) inside tower buildings, based on the ray tracing (RT) method and machine learning (ML) theories, a cluster-based chan...

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Autores principales:	Wenping Xie, Xiaomin Chen, Kai Mao, Yuxin Liu, Lugao Yin, Sheng Fang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	bit error rate (BER) capacity channel model clustering algorithm ray tracing (RT) tower buildings Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/5227ea5bf3ef40168276283f712f91b7
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id	oai:doaj.org-article:5227ea5bf3ef40168276283f712f91b7
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spelling	oai:doaj.org-article:5227ea5bf3ef40168276283f712f91b72021-11-25T19:07:11ZChannel Modeling and Analysis for the Sensor Network Inside Tower Buildings10.3390/sym131121542073-8994https://doaj.org/article/5227ea5bf3ef40168276283f712f91b72021-11-01T00:00:00Zhttps://www.mdpi.com/2073-8994/13/11/2154https://doaj.org/toc/2073-8994Symmetry-based channel digital twin is a great technology which can reproduce the communication channel of real scenes for performance evaluation of the wireless sensor network (WSN) inside tower buildings, based on the ray tracing (RT) method and machine learning (ML) theories, a cluster-based channel model is proposed in this paper. Meanwhile, an improved k-means method, which considers the weight of different dimensions in the multipath component distance (MCD) is presented for clustering, which has better clustering performance over the sparsity-based algorithm and traditional k-means algorithm. Moreover, the channel parameters such as cluster delay and cluster power are also investigated. On this basis, the communication performance of WSN, i.e., bit error rate (BER) and channel capacity are derived and analyzed. The simulation and analysis results show that the cluster model based on the RT method can get approximately equivalent channel impulse response (CIR), and the BER of proposed model is consistent with the simulated one. These results can provide reference for the node layout and optimization of WSN inside tower buildings.Wenping XieXiaomin ChenKai MaoYuxin LiuLugao YinSheng FangMDPI AGarticlebit error rate (BER)capacitychannel modelclustering algorithmray tracing (RT)tower buildingsMathematicsQA1-939ENSymmetry, Vol 13, Iss 2154, p 2154 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	bit error rate (BER) capacity channel model clustering algorithm ray tracing (RT) tower buildings Mathematics QA1-939
spellingShingle	bit error rate (BER) capacity channel model clustering algorithm ray tracing (RT) tower buildings Mathematics QA1-939 Wenping Xie Xiaomin Chen Kai Mao Yuxin Liu Lugao Yin Sheng Fang Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
description	Symmetry-based channel digital twin is a great technology which can reproduce the communication channel of real scenes for performance evaluation of the wireless sensor network (WSN) inside tower buildings, based on the ray tracing (RT) method and machine learning (ML) theories, a cluster-based channel model is proposed in this paper. Meanwhile, an improved k-means method, which considers the weight of different dimensions in the multipath component distance (MCD) is presented for clustering, which has better clustering performance over the sparsity-based algorithm and traditional k-means algorithm. Moreover, the channel parameters such as cluster delay and cluster power are also investigated. On this basis, the communication performance of WSN, i.e., bit error rate (BER) and channel capacity are derived and analyzed. The simulation and analysis results show that the cluster model based on the RT method can get approximately equivalent channel impulse response (CIR), and the BER of proposed model is consistent with the simulated one. These results can provide reference for the node layout and optimization of WSN inside tower buildings.
format	article
author	Wenping Xie Xiaomin Chen Kai Mao Yuxin Liu Lugao Yin Sheng Fang
author_facet	Wenping Xie Xiaomin Chen Kai Mao Yuxin Liu Lugao Yin Sheng Fang
author_sort	Wenping Xie
title	Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
title_short	Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
title_full	Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
title_fullStr	Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
title_full_unstemmed	Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
title_sort	channel modeling and analysis for the sensor network inside tower buildings
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/5227ea5bf3ef40168276283f712f91b7
work_keys_str_mv	AT wenpingxie channelmodelingandanalysisforthesensornetworkinsidetowerbuildings AT xiaominchen channelmodelingandanalysisforthesensornetworkinsidetowerbuildings AT kaimao channelmodelingandanalysisforthesensornetworkinsidetowerbuildings AT yuxinliu channelmodelingandanalysisforthesensornetworkinsidetowerbuildings AT lugaoyin channelmodelingandanalysisforthesensornetworkinsidetowerbuildings AT shengfang channelmodelingandanalysisforthesensornetworkinsidetowerbuildings
_version_	1718410277830000640

Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings

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