الفهرس 
Highlighted Game Theory under Cognitive Radio NetworkOnly 14 pages are availabe for public view
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Abstract
Existing Spectrum is traditionally assigned according to license policies and applications. Licensed spectrum accessing is not perfectly exploited in some locations at certain times. The policies of spectrum accessing are depended on transmission power, spectrum administrator, frequency band and duration of license. Advanced technologies in Cognitive Radio (CR) are used to provide flexibility in spectrum usage by allowing to unlicensed users to accesses the spectrum under certain conditions.
In CR networks, licensed (Primary) and unlicensed (secondary) users / providers use the same spectrum according to a certain arrangements and constrains for efficient spectrum utilization. This thesis investigates the problem of spectrum sharing or spectrum trading from game theory point of view to satisfy requirements of improving spectrum utilization in cooperative and non-cooperative pricing scheme.
In addition, thesis considers problem of non-cooperative power allocation and pricing scheme in Ad-Hoc cognitive network to ensure QoS constrains.
Our work introduces solution of mentioned problems using Game Theory Modelling and artificial intelligent algorithm (AI).
The first problem of non-cooperative spectrum sharing, Game theory provides economic solution for pricing strategies. The problem is mapped to player as primary service provider (PSP) in non-cooperative game; each player tries to sell spectrum with lower pricing strategy for more pricing gain. The intelligent algorithm with model constrains tries to find equilibrium state (Nash Equilibrium) such that there is no incentive to deviate. Moreover, Market-Equilibrium pricing model satisfies Nash Equilibrium Point (NEP) through analytic analysis of spectrum demand from unlicensed user and the spectrum supply from licensed users. In addition, Bertrand model will be solved as cooperative model to maximize total payoff. Then, cooperative performance will be compared with the non-cooperative performance.
The second problem of non-cooperative pricing strategies based on power allocation problem. The problem is modelled non-cooperatively between Ad-Hoc unlicensed users that try
to use high transmission power strategy that causes interference. The solution using AI under rate constrains and allocated pricing satisfies convergence of Nash Equilibrium (NE) and fairness. The fairness is accomplished by assigning low pricing for the high transmission power and increasing the average payoff of network.