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Comparative Study of RMSE and Functional Composition of Residual - Based Tuning of Hata Pathloss Model in the Suburban Area

Received: 16 October 2016    Accepted: 4 January 2017    Published: 29 January 2017
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Abstract

In this paper, RMSE and functional composition of residual are used as correction factors for tuning Hata model in the suburban area and 800-900MHz GSM frequency band. The study is based on empirical measurements conducted at Abak town, a suburban area in Akwa Ibom state, Nigeria. The tuned model is obtained by adding the correction factor to the original Hata pathloss model for the suburban area. The results showed that the functional composition of residual - based tuning approach has better prediction performance when compared with the RMSE-based tuning approach. Particularly, when the functional composition tuning approach is employed Hata model has the lowest RMSE value of 4.47, the highest prediction accuracy of 97.19% and the highest competitive success rate of 64.29%. On the other hand, the RMSE-tuned Hata model has a higher RMSE value of 7.03, lower prediction accuracy of 96.19% and the lower competitive success rate of 35.71%.

Published in International Journal of Systems Science and Applied Mathematics (Volume 2, Issue 1)
DOI 10.11648/j.ijssam.20170201.14
Page(s) 30-35
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), 2024. Published by Science Publishing Group

Keywords

Pathloss, Empirical Model, Functional Composition, Residual, Prediction Accuracy, Competitive Success Rate, Hata Model

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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Cite This Article
  • APA Style

    Wali Samuel, Nwiido Friday, Udoka Uduak Etim. (2017). Comparative Study of RMSE and Functional Composition of Residual - Based Tuning of Hata Pathloss Model in the Suburban Area. International Journal of Systems Science and Applied Mathematics, 2(1), 30-35. https://doi.org/10.11648/j.ijssam.20170201.14

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    ACS Style

    Wali Samuel; Nwiido Friday; Udoka Uduak Etim. Comparative Study of RMSE and Functional Composition of Residual - Based Tuning of Hata Pathloss Model in the Suburban Area. Int. J. Syst. Sci. Appl. Math. 2017, 2(1), 30-35. doi: 10.11648/j.ijssam.20170201.14

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    AMA Style

    Wali Samuel, Nwiido Friday, Udoka Uduak Etim. Comparative Study of RMSE and Functional Composition of Residual - Based Tuning of Hata Pathloss Model in the Suburban Area. Int J Syst Sci Appl Math. 2017;2(1):30-35. doi: 10.11648/j.ijssam.20170201.14

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  • @article{10.11648/j.ijssam.20170201.14,
      author = {Wali Samuel and Nwiido Friday and Udoka Uduak Etim},
      title = {Comparative Study of RMSE and Functional Composition of Residual - Based Tuning of Hata Pathloss Model in the Suburban Area},
      journal = {International Journal of Systems Science and Applied Mathematics},
      volume = {2},
      number = {1},
      pages = {30-35},
      doi = {10.11648/j.ijssam.20170201.14},
      url = {https://doi.org/10.11648/j.ijssam.20170201.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20170201.14},
      abstract = {In this paper, RMSE and functional composition of residual are used as correction factors for tuning Hata model in the suburban area and 800-900MHz GSM frequency band. The study is based on empirical measurements conducted at Abak town, a suburban area in Akwa Ibom state, Nigeria. The tuned model is obtained by adding the correction factor to the original Hata pathloss model for the suburban area. The results showed that the functional composition of residual - based tuning approach has better prediction performance when compared with the RMSE-based tuning approach. Particularly, when the functional composition tuning approach is employed Hata model has the lowest RMSE value of 4.47, the highest prediction accuracy of 97.19% and the highest competitive success rate of 64.29%. On the other hand, the RMSE-tuned Hata model has a higher RMSE value of 7.03, lower prediction accuracy of 96.19% and the lower competitive success rate of 35.71%.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Comparative Study of RMSE and Functional Composition of Residual - Based Tuning of Hata Pathloss Model in the Suburban Area
    AU  - Wali Samuel
    AU  - Nwiido Friday
    AU  - Udoka Uduak Etim
    Y1  - 2017/01/29
    PY  - 2017
    N1  - https://doi.org/10.11648/j.ijssam.20170201.14
    DO  - 10.11648/j.ijssam.20170201.14
    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  - 30
    EP  - 35
    PB  - Science Publishing Group
    SN  - 2575-5803
    UR  - https://doi.org/10.11648/j.ijssam.20170201.14
    AB  - In this paper, RMSE and functional composition of residual are used as correction factors for tuning Hata model in the suburban area and 800-900MHz GSM frequency band. The study is based on empirical measurements conducted at Abak town, a suburban area in Akwa Ibom state, Nigeria. The tuned model is obtained by adding the correction factor to the original Hata pathloss model for the suburban area. The results showed that the functional composition of residual - based tuning approach has better prediction performance when compared with the RMSE-based tuning approach. Particularly, when the functional composition tuning approach is employed Hata model has the lowest RMSE value of 4.47, the highest prediction accuracy of 97.19% and the highest competitive success rate of 64.29%. On the other hand, the RMSE-tuned Hata model has a higher RMSE value of 7.03, lower prediction accuracy of 96.19% and the lower competitive success rate of 35.71%.
    VL  - 2
    IS  - 1
    ER  - 

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Author Information
  • Department of Electrical/Electronic and Computer Engineering, University of Uyo, Uyo Nigeria

  • Department of Electrical/Electronic and Computer Engineering, University of Uyo, Uyo Nigeria

  • Department of Electrical/Electronic and Computer Engineering, University of Uyo, Uyo Nigeria

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