Estimation of α-κ-μ mobile fading channel parameters using evolutionary algorithms

This paper proposes the use of evolutionary algorithms (EAs) to estimate the physical parameters of the generalized α - κ - μ 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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Telecommunication systems 2021-05, Vol.77 (1), p.189-211
Hauptverfasser: Lemos, Carlos Paula, Veiga, Antônio Cláudio Paschoarelli, Fasolo, Sandro Adriano
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper proposes the use of evolutionary algorithms (EAs) to estimate the physical parameters of the generalized α - κ - μ 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 α - κ - μ 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 α - κ - μ 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.
ISSN:1018-4864
1572-9451
DOI:10.1007/s11235-020-00743-0