Path-Loss Estimation for Wireless Cellular Networks Using Okumura/Hata Model
Science Journal of Circuits, Systems and Signal Processing
Volume 7, Issue 1, March 2018, Pages: 20-27
Received: Nov. 30, 2017; Accepted: Dec. 9, 2017; Published: Jan. 11, 2018
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Ibrahim Mohamed, Electrical and Electronic Department, Faculty of Engineering, Omar Al-Mukhtar University, Al-Beida, Libya
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In cellular networks, accurate path-loss estimation is highly desirable not only to improve the performance but also to realize precise estimation of financial feasibility. In other words, while accurate path-loss estimation helps to achieve an acceptable performance and reasonable cost, inaccurate path-loss estimation would either lead to degrade the performance, or increase the cost. Different models were introduced in the literature for achieving accurate path-loss estimation. One of theses models is the Okumura/Hata model which is recommended for being used to estimate the path-loss in the cellular systems that employing micro-cells. It is characterized by its suitability for being used in a variety of environments. The main objective in this paper is to provide a guide line for path-loss estimation analysis using Okumura/Hata model. Matlab software was used to perform this analysis. Compared with free space model in which frequency and separation distance are the only contributors for path-loss, more accurate estimation can be achieved when Okumura/Hata model is used as it includes further correction factors, such as mobile station antenna height and base station antenna height.
Cellular Networks (CNs), Path-Loss Estimation Models, Free Space Propagation Model, Okumura/Hata Model
To cite this article
Ibrahim Mohamed, Path-Loss Estimation for Wireless Cellular Networks Using Okumura/Hata Model, Science Journal of Circuits, Systems and Signal Processing. Vol. 7, No. 1, 2018, pp. 20-27. doi: 10.11648/j.cssp.20180701.13
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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