Path Loss Prediction Model Development in a Mountainous Forest Environment

We consider a method for developing a radio-wave propagation prediction model in a mountainous forested area. A new path loss development approach uses a free-space path loss (FSPL) model and an empirical path loss model. To improve the prediction accuracy, the transmission path distance, free space...

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Autores principales:	Bilguunmaa Myagmardulam, Nakayama Tadachika, Kazuyoshi Takahashi, Ryu Miura, Fumie Ono, Toshinori Kagawa, Lin Shan, Fumihide Kojima
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Digital surface model LoRa path loss prediction modified empirical model drone mapper Telecommunication TK5101-6720 Transportation and communications HE1-9990
Acceso en línea:	https://doaj.org/article/d7ef03bffbc248a88ceb43af00c1a07c
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id	oai:doaj.org-article:d7ef03bffbc248a88ceb43af00c1a07c
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spelling	oai:doaj.org-article:d7ef03bffbc248a88ceb43af00c1a07c2021-11-18T00:11:30ZPath Loss Prediction Model Development in a Mountainous Forest Environment2644-125X10.1109/OJCOMS.2021.3122286https://doaj.org/article/d7ef03bffbc248a88ceb43af00c1a07c2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9586048/https://doaj.org/toc/2644-125XWe consider a method for developing a radio-wave propagation prediction model in a mountainous forested area. A new path loss development approach uses a free-space path loss (FSPL) model and an empirical path loss model. To improve the prediction accuracy, the transmission path distance, free space area, and forest area were calculated separately. We obtained the transmission path distance for free space and forest areas from the digital surface model (DSM), which represents surface elevation information, including vegetation and object height. In this study, the results showed that by combining the empirical model with FSPL for free space area, the accuracy for all the empirical models was improved. We confirmed that the transmission distance calculation of the free space area and forest area with a combination of the empirical models showed a better performance than the model with physical distance. The predicted model results were validated using the actual radio wave propagation in the 920 MHz band measurement data. The overall path loss prediction accuracy was improved for the empirical models average of 8.05 dB on the experimental data.Bilguunmaa MyagmardulamNakayama TadachikaKazuyoshi TakahashiRyu MiuraFumie OnoToshinori KagawaLin ShanFumihide KojimaIEEEarticleDigital surface modelLoRapath loss predictionmodified empirical modeldrone mapperTelecommunicationTK5101-6720Transportation and communicationsHE1-9990ENIEEE Open Journal of the Communications Society, Vol 2, Pp 2494-2501 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Digital surface model LoRa path loss prediction modified empirical model drone mapper Telecommunication TK5101-6720 Transportation and communications HE1-9990
spellingShingle	Digital surface model LoRa path loss prediction modified empirical model drone mapper Telecommunication TK5101-6720 Transportation and communications HE1-9990 Bilguunmaa Myagmardulam Nakayama Tadachika Kazuyoshi Takahashi Ryu Miura Fumie Ono Toshinori Kagawa Lin Shan Fumihide Kojima Path Loss Prediction Model Development in a Mountainous Forest Environment
description	We consider a method for developing a radio-wave propagation prediction model in a mountainous forested area. A new path loss development approach uses a free-space path loss (FSPL) model and an empirical path loss model. To improve the prediction accuracy, the transmission path distance, free space area, and forest area were calculated separately. We obtained the transmission path distance for free space and forest areas from the digital surface model (DSM), which represents surface elevation information, including vegetation and object height. In this study, the results showed that by combining the empirical model with FSPL for free space area, the accuracy for all the empirical models was improved. We confirmed that the transmission distance calculation of the free space area and forest area with a combination of the empirical models showed a better performance than the model with physical distance. The predicted model results were validated using the actual radio wave propagation in the 920 MHz band measurement data. The overall path loss prediction accuracy was improved for the empirical models average of 8.05 dB on the experimental data.
format	article
author	Bilguunmaa Myagmardulam Nakayama Tadachika Kazuyoshi Takahashi Ryu Miura Fumie Ono Toshinori Kagawa Lin Shan Fumihide Kojima
author_facet	Bilguunmaa Myagmardulam Nakayama Tadachika Kazuyoshi Takahashi Ryu Miura Fumie Ono Toshinori Kagawa Lin Shan Fumihide Kojima
author_sort	Bilguunmaa Myagmardulam
title	Path Loss Prediction Model Development in a Mountainous Forest Environment
title_short	Path Loss Prediction Model Development in a Mountainous Forest Environment
title_full	Path Loss Prediction Model Development in a Mountainous Forest Environment
title_fullStr	Path Loss Prediction Model Development in a Mountainous Forest Environment
title_full_unstemmed	Path Loss Prediction Model Development in a Mountainous Forest Environment
title_sort	path loss prediction model development in a mountainous forest environment
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/d7ef03bffbc248a88ceb43af00c1a07c
work_keys_str_mv	AT bilguunmaamyagmardulam pathlosspredictionmodeldevelopmentinamountainousforestenvironment AT nakayamatadachika pathlosspredictionmodeldevelopmentinamountainousforestenvironment AT kazuyoshitakahashi pathlosspredictionmodeldevelopmentinamountainousforestenvironment AT ryumiura pathlosspredictionmodeldevelopmentinamountainousforestenvironment AT fumieono pathlosspredictionmodeldevelopmentinamountainousforestenvironment AT toshinorikagawa pathlosspredictionmodeldevelopmentinamountainousforestenvironment AT linshan pathlosspredictionmodeldevelopmentinamountainousforestenvironment AT fumihidekojima pathlosspredictionmodeldevelopmentinamountainousforestenvironment
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Path Loss Prediction Model Development in a Mountainous Forest Environment

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