Game Theory Based Self-adaptive Power Control Algorithm for Cognitive Radio Networks

Abstract

Abstract: In order to meet all cognitive users' demands in the Cognitive Radio Networks(CRNs), non-cooperative game theory was used to model power control in the CRNs, and an adaptive power control algorithm for the CRNs was put forward using payoff unction and comprehensive cost function as utility function. Meanwhile, distances from the base station, stability of the algorithm and the interference between different cognitive users were considered. The existence and uniqueness of the Nash equilibrium were analyzed. By using the comprehensive cost function, each cognitive user in a non-cooperative game becomes cooperative and the Nash equilibrium can be convergent to Pareto-optimal solution. Comparing with other distributed algorithms, simulation results show that the proposed power control algorithm can overcome the near-far effect, greatly decrease the transmitting power of the cognitive users, and achieve fair spectrum share among users in the premise of meeting the SIR demand of different cognitive users.

Key words: cognitive wireless networks, power control, non-cooperative game theory, self-adaptive

CLC Number:

TN915.5

Ma Zhonggui, Ban Sha, Chen Guimei, Chen Linqi. Game Theory Based Self-adaptive Power Control Algorithm for Cognitive Radio Networks[J]. Journal of System Simulation, 2015, 27(3): 584-590.

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