Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas

Steve Worgu; Samuel Godwin Ajumo; Njumoke N. Odu

doi:doi:10.11648/j.ijssam.20170201.16

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Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas

Steve Worgu, Samuel Godwin Ajumo, Njumoke N. Odu

Published in International Journal of Systems Science and Applied Mathematics (Volume 2, Issue 1)

Received: 31 October 2016 Accepted: 5 January 2017 Published: 23 February 2017

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Abstract

In this paper, comparative evaluation of the pathloss prediction performance of the popular Hata-Okumura model for urban, suburban and rural areas is carried out. The study is based on empirical measurements conducted at Imo state university campus for 800 MHz GSM network. The prediction performance of the three categories of the Hata-Okumura model is analyzed and compared in terms of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Prediction Accuracy (PA). The results showed that the Hata-Okumura model for the Urban area has the best prediction accuracy when not optimised but it has the lowest optimised prediction accuracy. On the other hand the Hata-Okumura model for the rural/open area has the least prediction accuracy when not optimised but it has the highest prediction accuracy when it is optimised. The results show that adoption of a model because it has the highest prediction accuracy is not the best approach to the selection of pathloss models. Rather the models should be optimised and the best optimised model should be adopted.

Published in	International Journal of Systems Science and Applied Mathematics (Volume 2, Issue 1)
DOI	10.11648/j.ijssam.20170201.16
Page(s)	42-50
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Pathloss, Hata-Okumura Model, Pathloss Model, Model Tuning, Least Square Method

References

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[3]	Gupta, S. (2013, September). Comparative Pathloss Analysis Of Okumura And COST 231 Models For Wireless Mobile Communication Using MATLAB Simulation. In International Journal of Engineering Research and Technology (Vol. 2, No. 3 (March-2013)). ESRSA Publications.
[4]	Alim, M. A., Rahman, M. M., Hossain, M. M., & Nahid, A. A. (2010). Analysis of Large Scale Propagation Models for Mobile Communications in Urban Area. arXiv preprint arXiv: 1002. 2187.
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[7]	Abhayawardhana, V. S., Wassell, I. J., Crosby, D., Sellars, M. P., & Brown, M. G. (2005, May). Comparison of empirical propagation pathloss models for fixed wireless access systems. In Vehicular Technology Conference, 2005. VTC 2005-Spring. 2005 IEEE 61st (Vol. 1, pp. 73-77). IEEE.
[8]	Kostanic, I., Guerra, I., Faour, N., Zec, J., & Susanj, M. (2003). Optimization and Application of WCY Lee Micro-cell Propagation Model in 850MHz Frequency Band. In Proceedings of Wireless Networking Symposium.
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[15]	Okumura, Y., Ohmori, E., Kawano, T., & Fukuda, K. (1968). Field strength and its variability in VHF and UHF land-mobile radio service. Rev. Elec. Commun. Lab, 16 (9), 825-73.
[16]	Ogbulezie, J. C., Onuu, M. U., Ushie, J. O., & Usibe, B. E. (2013). Propagation models for GSM 900 and 1800 MHz for Port Harcourt and Enugu, Nigeria. Network and Communication Technologies, 2 (2), 1.
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APA Style

Steve Worgu, Samuel Godwin Ajumo, Njumoke N. Odu. (2017). Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas. International Journal of Systems Science and Applied Mathematics, 2(1), 42-50. https://doi.org/10.11648/j.ijssam.20170201.16

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ACS Style

Steve Worgu; Samuel Godwin Ajumo; Njumoke N. Odu. Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas. Int. J. Syst. Sci. Appl. Math. 2017, 2(1), 42-50. doi: 10.11648/j.ijssam.20170201.16

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AMA Style

Steve Worgu, Samuel Godwin Ajumo, Njumoke N. Odu. Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas. Int J Syst Sci Appl Math. 2017;2(1):42-50. doi: 10.11648/j.ijssam.20170201.16

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@article{10.11648/j.ijssam.20170201.16,
  author = {Steve Worgu and Samuel Godwin Ajumo and Njumoke N. Odu},
  title = {Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas},
  journal = {International Journal of Systems Science and Applied Mathematics},
  volume = {2},
  number = {1},
  pages = {42-50},
  doi = {10.11648/j.ijssam.20170201.16},
  url = {https://doi.org/10.11648/j.ijssam.20170201.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20170201.16},
  abstract = {In this paper, comparative evaluation of the pathloss prediction performance of the popular Hata-Okumura model for urban, suburban and rural areas is carried out. The study is based on empirical measurements conducted at Imo state university campus for 800 MHz GSM network. The prediction performance of the three categories of the Hata-Okumura model is analyzed and compared in terms of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Prediction Accuracy (PA). The results showed that the Hata-Okumura model for the Urban area has the best prediction accuracy when not optimised but it has the lowest optimised prediction accuracy. On the other hand the Hata-Okumura model for the rural/open area has the least prediction accuracy when not optimised but it has the highest prediction accuracy when it is optimised. The results show that adoption of a model because it has the highest prediction accuracy is not the best approach to the selection of pathloss models. Rather the models should be optimised and the best optimised model should be adopted.},
 year = {2017}
}

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TY  - JOUR
T1  - Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas
AU  - Steve Worgu
AU  - Samuel Godwin Ajumo
AU  - Njumoke N. Odu
Y1  - 2017/02/23
PY  - 2017
N1  - https://doi.org/10.11648/j.ijssam.20170201.16
DO  - 10.11648/j.ijssam.20170201.16
T2  - International Journal of Systems Science and Applied Mathematics
JF  - International Journal of Systems Science and Applied Mathematics
JO  - International Journal of Systems Science and Applied Mathematics
SP  - 42
EP  - 50
PB  - Science Publishing Group
SN  - 2575-5803
UR  - https://doi.org/10.11648/j.ijssam.20170201.16
AB  - In this paper, comparative evaluation of the pathloss prediction performance of the popular Hata-Okumura model for urban, suburban and rural areas is carried out. The study is based on empirical measurements conducted at Imo state university campus for 800 MHz GSM network. The prediction performance of the three categories of the Hata-Okumura model is analyzed and compared in terms of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Prediction Accuracy (PA). The results showed that the Hata-Okumura model for the Urban area has the best prediction accuracy when not optimised but it has the lowest optimised prediction accuracy. On the other hand the Hata-Okumura model for the rural/open area has the least prediction accuracy when not optimised but it has the highest prediction accuracy when it is optimised. The results show that adoption of a model because it has the highest prediction accuracy is not the best approach to the selection of pathloss models. Rather the models should be optimised and the best optimised model should be adopted.
VL  - 2
IS  - 1
ER  -

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Author Information

Steve Worgu

Department of Electrical/Computer Engineering, Port Harcourt Polytechnic, Rumuola, Port Harcourt, Nigeria
Samuel Godwin Ajumo

Department of Electrical/Computer Engineering, Port Harcourt Polytechnic, Rumuola, Port Harcourt, Nigeria
Njumoke N. Odu

Department of Electrical/Computer Engineering, Port Harcourt Polytechnic, Rumuola, Port Harcourt, Nigeria

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Plain Text BibTeX RIS

APA Style

Steve Worgu, Samuel Godwin Ajumo, Njumoke N. Odu. (2017). Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas. International Journal of Systems Science and Applied Mathematics, 2(1), 42-50. https://doi.org/10.11648/j.ijssam.20170201.16

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ACS Style

Steve Worgu; Samuel Godwin Ajumo; Njumoke N. Odu. Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas. Int. J. Syst. Sci. Appl. Math. 2017, 2(1), 42-50. doi: 10.11648/j.ijssam.20170201.16

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AMA Style

Steve Worgu, Samuel Godwin Ajumo, Njumoke N. Odu. Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas. Int J Syst Sci Appl Math. 2017;2(1):42-50. doi: 10.11648/j.ijssam.20170201.16

Copy | Download

@article{10.11648/j.ijssam.20170201.16,
  author = {Steve Worgu and Samuel Godwin Ajumo and Njumoke N. Odu},
  title = {Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas},
  journal = {International Journal of Systems Science and Applied Mathematics},
  volume = {2},
  number = {1},
  pages = {42-50},
  doi = {10.11648/j.ijssam.20170201.16},
  url = {https://doi.org/10.11648/j.ijssam.20170201.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20170201.16},
  abstract = {In this paper, comparative evaluation of the pathloss prediction performance of the popular Hata-Okumura model for urban, suburban and rural areas is carried out. The study is based on empirical measurements conducted at Imo state university campus for 800 MHz GSM network. The prediction performance of the three categories of the Hata-Okumura model is analyzed and compared in terms of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Prediction Accuracy (PA). The results showed that the Hata-Okumura model for the Urban area has the best prediction accuracy when not optimised but it has the lowest optimised prediction accuracy. On the other hand the Hata-Okumura model for the rural/open area has the least prediction accuracy when not optimised but it has the highest prediction accuracy when it is optimised. The results show that adoption of a model because it has the highest prediction accuracy is not the best approach to the selection of pathloss models. Rather the models should be optimised and the best optimised model should be adopted.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Comparative Evaluation of the Pathloss Prediction Performance Hata-Okumura Pathloss Model for Urban, Suburban and Rural Areas
AU  - Steve Worgu
AU  - Samuel Godwin Ajumo
AU  - Njumoke N. Odu
Y1  - 2017/02/23
PY  - 2017
N1  - https://doi.org/10.11648/j.ijssam.20170201.16
DO  - 10.11648/j.ijssam.20170201.16
T2  - International Journal of Systems Science and Applied Mathematics
JF  - International Journal of Systems Science and Applied Mathematics
JO  - International Journal of Systems Science and Applied Mathematics
SP  - 42
EP  - 50
PB  - Science Publishing Group
SN  - 2575-5803
UR  - https://doi.org/10.11648/j.ijssam.20170201.16
AB  - In this paper, comparative evaluation of the pathloss prediction performance of the popular Hata-Okumura model for urban, suburban and rural areas is carried out. The study is based on empirical measurements conducted at Imo state university campus for 800 MHz GSM network. The prediction performance of the three categories of the Hata-Okumura model is analyzed and compared in terms of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Prediction Accuracy (PA). The results showed that the Hata-Okumura model for the Urban area has the best prediction accuracy when not optimised but it has the lowest optimised prediction accuracy. On the other hand the Hata-Okumura model for the rural/open area has the least prediction accuracy when not optimised but it has the highest prediction accuracy when it is optimised. The results show that adoption of a model because it has the highest prediction accuracy is not the best approach to the selection of pathloss models. Rather the models should be optimised and the best optimised model should be adopted.
VL  - 2
IS  - 1
ER  -

Copy | Download