A game theoretic approach for resource allocation in Cognitive Wireless Sensor Networks

Game theoretic adaptive algorithms can be successfully applied for distributed intelligent Cognitive Wireless Sensor Networks (CWSNs). The use of these algorithms avoids weaknesses of centralized CWSNs. In this paper, a noncooperative spectrum sharing game theoretic approach for CWSNs is proposed to determine the optimum spectrum demand. The main objectives of this approach are improving the flexibility, efficiency and fairness in spectrum allocation with guaranteed sum data rates. We introduce a rewarding scheme in this approach to promote the communication of the sensor nodes that have good channel qualities and residual power levels. Then we analyze the existence and the uniqueness of the Nash Equilibrium. The simulation results show that the energy efficiency of our method is higher than the traditional uniform Time Division Multiplexing (TDMA - Uniform) approach and traditional TDMA approach that depends on channel (TDMA - Channel Based).