Goal-Pareto Based NSGA for Optimal Reconfiguration of Cognitive Radio Systems

TLDR: A novel optimization algorithm named goal-pareto based non-dominated sorting genetic algorithm (GBNSGA) has a role of playing an optimal reconfiguration of agile cognitive radio system by altering set of modem parameters designated as knobs working in dynamic wireless environment.

Abstract: This paper proposes a novel optimization algorithm named goal-pareto based non-dominated sorting genetic algorithm (GBNSGA). The proposed technique has a role of playing an optimal reconfiguration of agile cognitive radio (CR) system by altering set of modem parameters designated as knobs working in dynamic wireless environment. Recently, various kinds of bio-inspired algorithms either timely or costly efficient have been investigated so as to accomplish a smart way of switching the radio configuration. Towards this, the proposed GBNSGA in this paper performs a hybrid type of optimization process from a functional point of view, namely well-known pareto-based non-dominated sorting genetic algorithm (NSGA) performs with goal programming (GP) cooperatively. To confirm the validity, a realistic scenario covering cdma2000 forward link for the class of conversational audio service delivered in Rician channel is set to be considered. By conducting computer simulations, the figure of merits of the proposed algorithm will be exploited regarding how many sets of not over-maximizing systems are achieved residing in range of prescribed performance goals after an optimization procedure. Among those, the optimal configuration can be achieved in the sense of consuming low transmit power, while obeying required quality of service.