Investigation of Pricing Issue Using Different Game Models in Cognitive Radio Network

Abstract

Cognitive radio (CR) is wireless communication system that aims to introduce service to unlicensed users or secondary users (SUs) without harming operation of licensed users or primary users (PUs). Hence, the idea behind CR is to exploit unused resources of PUs at time or frequency at which PUs is not effected. Spectrum utilization can be accomplished by sharing of spectrum holes from (PUs) or primary service providers (PSPs) to (SUs) or secondary service provider (SSPs). Actually, spectrum sharing is considered as trading process in which spectrum seller charge free spectrum holes for spectrum buyers whom willing to buy spectrum for specified taxation called price. In this paper, pricing or (taxation) issue will be investigated through two different pricing schemes, namely, market-equilibrium and Bertrand competitive market. In market-equilibrium, the pricing depends on satisfying spectrum demand from SSPs/SUs by spectrum supply of PSPs. It is solved and analyzed in simplified way that reduces computational. Moreover, effect of bandwidth requirement of PUs on spectrum sharing will be studied. In Bertrand competitive market, PSPs tries to accomplish highest gain or payoff regarding to others by manipulating in price. In addition, genetic algorithm (GA) will be proposed with Bertrand competitive model to optimize pricing process to unique Nash Equilibrium by convergence with reducing abrupt change in price. GA improves best response strategy selection through reproduction process. Also, it reduces average pricing charged to SSP/SUs and this considered as attractive parameter for more spectrum selling and more gain to PSPs comparing round-robin algorithm.