Path Loss Model Optimization Using Stochastic Hybrid Genetic Algorithm

  • Authors

    • A. Bhuvaneshwari
    • R. Hemalatha
    • T. SatyaSavithri
    2018-10-02
    https://doi.org/10.14419/ijet.v7i4.10.21041
  • Cost 231 Hata model, Genetic algorithm, Path Loss, Root Mean Square Error, Weighted Least Square.

  • Abstract

    In the context of modeling the propagation of mobile radio signals, optimizing the existing path loss model is largely required to precisely represent the actual propagation medium. In this paper, a hybrid tuning approach is proposed by merging the stochastic Weighted Least Square method and Genetic algorithm. The proposed hybrid optimization is employed to optimize the parameters of Cost 231 Hata propagation model and is validated by cellular field strength measurements at 900 MHz in the sub urban region. The hybrid optimization is compared with optimized results of Weighted Least Square method and Genetic algorithm. The least values of Mean Square error (0.2702), RMSE (0.4798) and percentage Relative error (3.96) justify the tuning precision of the hybrid method. The proposed optimization approach could be used by network service providers to improve the quality of service and in mobile radio network planning of 900 MHz band for 4G LTE services.

     

     

  • References

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  • How to Cite

    Bhuvaneshwari, A., Hemalatha, R., & SatyaSavithri, T. (2018). Path Loss Model Optimization Using Stochastic Hybrid Genetic Algorithm. International Journal of Engineering & Technology, 7(4.10), 464-469. https://doi.org/10.14419/ijet.v7i4.10.21041

    Received date: 2018-10-05

    Accepted date: 2018-10-05

    Published date: 2018-10-02