Performance Evaluation of Hata-Davidson Pathloss Model Tuning Approaches for a Suburban Area
American Journal of Software Engineering and Applications
Volume 6, Issue 3, June 2017, Pages: 93-98
Received: Jan. 3, 2017; Accepted: Jan. 18, 2017; Published: Jun. 23, 2017
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Authors
Wali Samuel, Department of Electrical/Electronic and Computer Engineering, University of Uyo, Uyo, Nigeria
Njumoke N. Odu, Department of Electrical/Computer Engineering, Port Harcourt Polytechnic, Port Harcourt, Nigeria
Samuel Godwin Ajumo, Department of Electrical/Computer Engineering, Port Harcourt Polytechnic, Port Harcourt, Nigeria
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Abstract
In this paper, comparative study of RMSE-base tuning and multi-parameter-based tuning of Hata-Davidson pathloss model for a suburban area is presented. The study was based on field measurement of received signal strength carried out in a suburban area for a GSM (Global System for Mobile communication) network that operates in the 1800MHz frequency band. The results show that multi-parameter-tuned Hata-Davidson model has better prediction accuracy of 98.70720432% and RMSE of 2.177522885 dB as against the RMSE-tuned Hata-Davidson model with prediction accuracy of 97.42722692% and RMSE of 4.256897001dB. However, the RMSE is quite simple and easier to implement even in embedded systems and systems with limited resource.
Keywords
Pathloss, Propagation Model, Hata-Davidson Model, Model Optimisation, Multi-Parameter-Based Tuning Method, RMSE-Base Tuning Method, Least Square Error Method
To cite this article
Wali Samuel, Njumoke N. Odu, Samuel Godwin Ajumo, Performance Evaluation of Hata-Davidson Pathloss Model Tuning Approaches for a Suburban Area, American Journal of Software Engineering and Applications. Vol. 6, No. 3, 2017, pp. 93-98. doi: 10.11648/j.ajsea.20170603.16
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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