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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Main Authors: Wenping Xie, Xiaomin Chen, Kai Mao, Yuxin Liu, Lugao Yin, Sheng Fang
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Symmetry
Subjects:
Online Access:https://www.mdpi.com/2073-8994/13/11/2154
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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
collection DOAJ
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.
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spelling doaj.art-5227ea5bf3ef40168276283f712f91b72023-11-23T01:45:57ZengMDPI AGSymmetry2073-89942021-11-011311215410.3390/sym13112154Channel Modeling and Analysis for the Sensor Network Inside Tower BuildingsWenping Xie0Xiaomin Chen1Kai Mao2Yuxin Liu3Lugao Yin4Sheng Fang5The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaThe Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaThe Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaThe Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaThe Beijing Institute of Astronautical Systems Engineering, Beijing 100076, ChinaThe Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaSymmetry-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.https://www.mdpi.com/2073-8994/13/11/2154bit error rate (BER)capacitychannel modelclustering algorithmray tracing (RT)tower buildings
spellingShingle Wenping Xie
Xiaomin Chen
Kai Mao
Yuxin Liu
Lugao Yin
Sheng Fang
Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
Symmetry
bit error rate (BER)
capacity
channel model
clustering algorithm
ray tracing (RT)
tower buildings
title 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_short Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
title_sort channel modeling and analysis for the sensor network inside tower buildings
topic bit error rate (BER)
capacity
channel model
clustering algorithm
ray tracing (RT)
tower buildings
url https://www.mdpi.com/2073-8994/13/11/2154
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