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Estimation of \(\alpha -\kappa -\mu \) mobile fading channel parameters using evolutionary algorithms

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Abstract

This paper proposes the use of evolutionary algorithms (EAs) to estimate the physical parameters of the generalized \(\alpha -\kappa -\mu \) mobile fading channel model. The estimation of parameters is a fundamental step that allows for the statistical model to adjust to the real experimental data. The The maximum likelihood estimation (MLE) method that is traditionally used for estimating parameters of the \(\alpha -\kappa -\mu \) channel uses nonlinear numerical methods. In some cases, the use of nonlinear numerical methods may lead the MLE to make physically unacceptable estimations, or even to not be able to obtain a result. Our proposal is to innovate the existing EAs by incorporating an adaptive approach, a new mutation strategy and an adequate fitness function for the estimation of \(\alpha -\kappa -\mu \) parameters. Experimental results are presented to confirm that parameters estimated by the EAs (genetic algorithms, differential evolution algorithms, and differential evolution algorithms with an adaptive guiding mechanism) are all physically acceptable. These experiments show that the EAs outperform MLE estimation results.

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Acknowledgements

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

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Authors and Affiliations

  1. Instituto Federal de Educação, Ciência e Tecnologia do Triângulo Mineiro, Patos de Minas, Brasil

    Carlos Paula Lemos

  2. Faculdade de Engenharia Elétrica, Universidade Federal de Uberlândia, Uberlândia, Brasil

    Antônio Cláudio Paschoarelli Veiga

  3. Universidade Federal de São João del Rei, Ouro Branco, Brasil

    Sandro Adriano Fasolo

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  1. Carlos Paula Lemos
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Correspondence to Carlos Paula Lemos.

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Lemos, C.P., Veiga, A.C.P. & Fasolo, S.A. Estimation of \(\alpha -\kappa -\mu \) mobile fading channel parameters using evolutionary algorithms. Telecommun Syst 77, 189–211 (2021). https://doi.org/10.1007/s11235-020-00743-0

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