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Path loss dataset for modeling radio wave propagation in smart campus environment

Path loss models are often used by radio network engineers to predict signal coverage, optimize limited network resources, and perform interference feasibility studies. However, the propagation mechanisms of electromagnetic waves depend on the physical characteristics of the wireless channel. Theref...

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Detalles Bibliográficos
Autores principales: Popoola, Segun I., Atayero, Aderemi A., Arausi, Oghenekaro D., Matthews, Victor O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988496/
https://www.ncbi.nlm.nih.gov/pubmed/29876462
http://dx.doi.org/10.1016/j.dib.2018.02.026
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author Popoola, Segun I.
Atayero, Aderemi A.
Arausi, Oghenekaro D.
Matthews, Victor O.
author_facet Popoola, Segun I.
Atayero, Aderemi A.
Arausi, Oghenekaro D.
Matthews, Victor O.
author_sort Popoola, Segun I.
collection PubMed
description Path loss models are often used by radio network engineers to predict signal coverage, optimize limited network resources, and perform interference feasibility studies. However, the propagation mechanisms of electromagnetic waves depend on the physical characteristics of the wireless channel. Therefore, efficient radio network planning and optimization requires detailed information about the specific propagation environment. In this data article, the path loss data and the corresponding information that are needed for modeling radio wave propagation in smart campus environment are presented and analyzed. Extensive drive test measurements are performed along three different routes (X, Y, and Z) within Covenant University, Ota, Ogun State, Nigeria (Latitude 6°40′30.3″N, Longitude 3°09′46.3″E) to record path loss data as the mobile receiver moves away from each of the three 1800 MHz base station transmitters involved. Also, the longitude, latitude, elevation, altitude, clutter height, and the distance information, which describes the smart campus environment, are obtained from Digital Terrain Map (DTM) in ATOLL radio network planning tool. Results of the first-order descriptive statistics and the frequency distributions of all the seven parameters are presented in tables and graphs respectively. In addition, correlation analyses are performed to understand the relationships between the network parameters and the terrain information. For ease of reuse, the comprehensive data are prepared in Microsoft Excel spreadsheet and attached to this data article. In essence, the availability of these data will facilitate the development of path loss models for efficient radio network planning and optimization in smart campus environment.
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spelling pubmed-59884962018-06-06 Path loss dataset for modeling radio wave propagation in smart campus environment Popoola, Segun I. Atayero, Aderemi A. Arausi, Oghenekaro D. Matthews, Victor O. Data Brief Engineering Path loss models are often used by radio network engineers to predict signal coverage, optimize limited network resources, and perform interference feasibility studies. However, the propagation mechanisms of electromagnetic waves depend on the physical characteristics of the wireless channel. Therefore, efficient radio network planning and optimization requires detailed information about the specific propagation environment. In this data article, the path loss data and the corresponding information that are needed for modeling radio wave propagation in smart campus environment are presented and analyzed. Extensive drive test measurements are performed along three different routes (X, Y, and Z) within Covenant University, Ota, Ogun State, Nigeria (Latitude 6°40′30.3″N, Longitude 3°09′46.3″E) to record path loss data as the mobile receiver moves away from each of the three 1800 MHz base station transmitters involved. Also, the longitude, latitude, elevation, altitude, clutter height, and the distance information, which describes the smart campus environment, are obtained from Digital Terrain Map (DTM) in ATOLL radio network planning tool. Results of the first-order descriptive statistics and the frequency distributions of all the seven parameters are presented in tables and graphs respectively. In addition, correlation analyses are performed to understand the relationships between the network parameters and the terrain information. For ease of reuse, the comprehensive data are prepared in Microsoft Excel spreadsheet and attached to this data article. In essence, the availability of these data will facilitate the development of path loss models for efficient radio network planning and optimization in smart campus environment. Elsevier 2018-02-16 /pmc/articles/PMC5988496/ /pubmed/29876462 http://dx.doi.org/10.1016/j.dib.2018.02.026 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Engineering
Popoola, Segun I.
Atayero, Aderemi A.
Arausi, Oghenekaro D.
Matthews, Victor O.
Path loss dataset for modeling radio wave propagation in smart campus environment
title Path loss dataset for modeling radio wave propagation in smart campus environment
title_full Path loss dataset for modeling radio wave propagation in smart campus environment
title_fullStr Path loss dataset for modeling radio wave propagation in smart campus environment
title_full_unstemmed Path loss dataset for modeling radio wave propagation in smart campus environment
title_short Path loss dataset for modeling radio wave propagation in smart campus environment
title_sort path loss dataset for modeling radio wave propagation in smart campus environment
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988496/
https://www.ncbi.nlm.nih.gov/pubmed/29876462
http://dx.doi.org/10.1016/j.dib.2018.02.026
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