Cognitive Radio Engine Design using Various Optimization Algorithms

Abstract

The concept of dynamic spectrum access addresses the problem of spectral scarcity resulting from the proliferation of wireless communications services and standards through a key technology, cognitive radio. The latter is considered to be an intelligent and autonomous device capable of making decisions to adapt to its dynamic environment in real time in order to meet the user's needs in terms of quality of service while respecting the regulatory framework in force. In this paper, we propose a comparative analysis of three optimization algorithms,out of based two are based on bio-inspired approaches, namely: the genetic algorithm, the particle swarm optimization, for the adaptation of the transmission parameters which has been formulated in the form of a multi-objective optimization problem. The results obtained through a series of tests and simulations clearly demonstrate a clear superiority of cultural algorithmin terms of output power, BER and channel attenuation compared to the techniques most used in the literature, namely genetic algorithm and the particle swarm optimization algorithm.