Comparison between Xia and Walfisch-Ikegami models for low-rise building path loss prediction

This paper presents path loss prediction on 2-D aerial images taken from the actual areas. The original Xia path loss model and the Walfisch-Ikegami model were applied for predicting in low rise building area. In case of the Xia model for non line of sight (NLOS), it requires a set of model paramete...

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Main Authors: Supachai Phaiboon, Pisit 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/123456789/28972
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spelling th-mahidol.289722018-09-24T15:59:10Z Comparison between Xia and Walfisch-Ikegami models for low-rise building path loss prediction Supachai Phaiboon Pisit Phokharatkul Mahidol University Computer Science Engineering This paper presents path loss prediction on 2-D aerial images taken from the actual areas. The original Xia path loss model and the Walfisch-Ikegami model were applied for predicting in low rise building area. In case of the Xia model for non line of sight (NLOS), it requires a set of model parameters such as distance from the last roof top to receiver, average building height, and antenna heights. While the Walfisch-Ikegami (WI) model requires road parameters such as road width and road orientation. We performed measurements at frequencies of 900 and 1800 MHz for comparison between the two approaches. From the results it is found that the Xia model provides good agreement, while the WI model provides good agreement especially when the receiver is on the street between two buildings. © 2010 IEEE. 2018-09-24T08:56:21Z 2018-09-24T08:56:21Z 2010-12-01 Conference Paper IEEE Region 10 Annual International Conference, Proceedings/TENCON. (2010), 889-892 10.1109/TENCON.2010.5686558 2-s2.0-79951617185 https://repository.li.mahidol.ac.th/handle/123456789/28972 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79951617185&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 Computer Science
Engineering
spellingShingle Computer Science
Engineering
Supachai Phaiboon
Pisit Phokharatkul
Comparison between Xia and Walfisch-Ikegami models for low-rise building path loss prediction
description This paper presents path loss prediction on 2-D aerial images taken from the actual areas. The original Xia path loss model and the Walfisch-Ikegami model were applied for predicting in low rise building area. In case of the Xia model for non line of sight (NLOS), it requires a set of model parameters such as distance from the last roof top to receiver, average building height, and antenna heights. While the Walfisch-Ikegami (WI) model requires road parameters such as road width and road orientation. We performed measurements at frequencies of 900 and 1800 MHz for comparison between the two approaches. From the results it is found that the Xia model provides good agreement, while the WI model provides good agreement especially when the receiver is on the street between two buildings. © 2010 IEEE.
author2 Mahidol University
author_facet Mahidol University
Supachai Phaiboon
Pisit Phokharatkul
format Conference or Workshop Item
author Supachai Phaiboon
Pisit Phokharatkul
author_sort Supachai Phaiboon
title Comparison between Xia and Walfisch-Ikegami models for low-rise building path loss prediction
title_short Comparison between Xia and Walfisch-Ikegami models for low-rise building path loss prediction
title_full Comparison between Xia and Walfisch-Ikegami models for low-rise building path loss prediction
title_fullStr Comparison between Xia and Walfisch-Ikegami models for low-rise building path loss prediction
title_full_unstemmed Comparison between Xia and Walfisch-Ikegami models for low-rise building path loss prediction
title_sort comparison between xia and walfisch-ikegami models for low-rise building path loss prediction
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/28972
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