Site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems

This paper presents a new model for the propagation prediction for mobile communication network inside building. The model is based on the determination of the dominant paths between the transmitter and the receiver, diffraction at the coner and wave-guiding effect. The field strength is predicted w...

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Main Authors: S. Phaiboon, P. Phokharatkul
Other Authors: Mahidol University
Format: Conference or Workshop Item
Published: 2018
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/21311
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Institution: Mahidol University
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spelling th-mahidol.213112018-07-24T10:41:12Z Site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems S. Phaiboon P. Phokharatkul Mahidol University Engineering This paper presents a new model for the propagation prediction for mobile communication network inside building. The model is based on the determination of the dominant paths between the transmitter and the receiver, diffraction at the coner and wave-guiding effect. The field strength is predicted with adaptive neuro - fuzzy inference systems (AKFIS), trained with measurements. The advantage of the ANFIS with hybrid least squares and gradient descent algorithms is fast convergence compared with original neural network The K-means algorithm for selection of training patterns is also used. Comparison of our predicted results to measurements indicate that improvements in accuracy over conventional empirical model are achieved. © 2004 IEEE. 2018-07-24T03:41:12Z 2018-07-24T03:41:12Z 2004-12-01 Conference Paper 2004 4th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2004. (2004), 154-157 2-s2.0-28844473270 https://repository.li.mahidol.ac.th/handle/123456789/21311 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=28844473270&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Engineering
spellingShingle Engineering
S. Phaiboon
P. Phokharatkul
Site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems
description This paper presents a new model for the propagation prediction for mobile communication network inside building. The model is based on the determination of the dominant paths between the transmitter and the receiver, diffraction at the coner and wave-guiding effect. The field strength is predicted with adaptive neuro - fuzzy inference systems (AKFIS), trained with measurements. The advantage of the ANFIS with hybrid least squares and gradient descent algorithms is fast convergence compared with original neural network The K-means algorithm for selection of training patterns is also used. Comparison of our predicted results to measurements indicate that improvements in accuracy over conventional empirical model are achieved. © 2004 IEEE.
author2 Mahidol University
author_facet Mahidol University
S. Phaiboon
P. Phokharatkul
format Conference or Workshop Item
author S. Phaiboon
P. Phokharatkul
author_sort S. Phaiboon
title Site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems
title_short Site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems
title_full Site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems
title_fullStr Site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems
title_full_unstemmed Site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems
title_sort site-specific indoor propagation prediction using adtive neuro-fuzzy inference systems
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/21311
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