Optimisation de la QoS dans un r{\'e}seau de radio cognitive en utilisant la m{\'e}taheuristique SFLA (Shuffled Frog Leaping Algorithm)

TL;DR

This paper explores optimizing QoS in cognitive radio networks using the SFLA metaheuristic to improve solutions for secondary user requirements in a multi-carrier environment.

Contribution

It introduces the application of the SFLA metaheuristic for QoS optimization in cognitive radio networks, aiming for better solutions in multi-carrier scenarios.

Findings

SFLA improves QoS solutions for secondary users.

Enhanced performance in multi-carrier cognitive radio networks.

Metaheuristic approach outperforms traditional methods.

Abstract

This work proposes a study of quality of service (QoS) in cognitive radio networks. This study is based on a stochastic optimization method called shuffled frog leaping algorithm (SFLA). The interest of the SFLA algorithm is to guarantee a better solution in a multi-carrier context in order to satisfy the requirements of the secondary user (SU).