Multi objective optimization of expense and revenue in a cognitive radio network using NSGA-II

Abstract

In this paper we consider an auction framework of cognitive radio network comprises of primary and secondary users (SU). The spectrum is divided into channels using frequency division multiple access (FDMA). Primary users have license to use the channels. When the channels are idle, primary users lease the vacant spectrum for monetary gain. Cognitive users or SUs bid for the channels. The purchaser who provides highest bid value is selected by primary user. Our objective is to maximize the revenue earned by primary users and to minimize the expense given by the secondary users. The problem is bi-objective and both the objectives are conflicting. Using Non dominated sorting genetic algorithm II; we solve both the objectives of primary and secondary users. The algorithm solves the problem well and find optimize values of both expense and revenue. © Springer-Verlag 2013.