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Comparison of Empirical Propagation Path Loss Models for Mobile Communication

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dc.creator Mollel, Michael
dc.creator Michael, Kisangiri
dc.date 2021-05-04T08:51:51Z
dc.date 2021-05-04T08:51:51Z
dc.date 2014
dc.date.accessioned 2022-10-25T09:15:47Z
dc.date.available 2022-10-25T09:15:47Z
dc.identifier https://dspace.nm-aist.ac.tz/handle/20.500.12479/1167
dc.identifier.uri http://hdl.handle.net/123456789/94607
dc.description This research article published by Computer Engineering and Intelligent Systems, Vol.5, No.9, 2014
dc.description Empirical propagation models have found favor in both research and industrial communities owing to their speed of execution and their limited reliance on detailed knowledge of the terrain. In mobile communication the accuracy prediction of path losses is a crucial element during network planning and optimization. However, the existence of multiple propagation models means that there is no propagation model which is precisely and accurate in prediction of path loss fit for every environs other than in which they were designed. This paper presents few empirical models suitable for path loss prediction in mobile communication. Experimental measurements of received power for the 900 MHz GSM system are made in urban, suburban, and rural areas of Dar es Salaam, Tanzania. Measured data are compared with those obtained by five prediction models: Stanford University Interim (SUI) models [1], the COST-231 Hata model [2], the ECC-33 model [3], the ERICSSON model [4], and the HATA-OKUMURA model [5]. The results show that in general the SUI, COST-231, ERICSSON, and Hata-Okumura under-predict the path loss in all environments, while the ECC-33 model shows the best results, especially in suburban and over-predict pathloss in urban area.
dc.format application/pdf
dc.language en
dc.publisher Computer Engineering and Intelligent Systems
dc.subject Propagation pathloss
dc.subject Empirical models
dc.subject Radio coverage
dc.subject Mobile communications.
dc.title Comparison of Empirical Propagation Path Loss Models for Mobile Communication
dc.type Article


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