Pricing Based Power Control Game for Cognitive Radio Networks

Cognitive Radio has been recently been proposed as a promising technology to improve the spectrum utilization efficiency by intelligently sensing and opportunely spectrum accessing some vacant bands of the primary users. In this paper, the power control problem in secondary system is modeled as a non-cooperative game model. To improve the secondary system's performance, a pricing function based on Signal-to-Interference and Noise Ratio (SINR) is incorporated into the non-cooperative power control game model, which referred as NPCGP in this paper. The existence, uniqueness and Pareto optimality of Nash Equilibrium (NE) for the proposed NPCGP model are proved. An iterative power allocation algorithm based on NPCGP mode is proposed in this paper. Simulation results show that the algorithm is robust and it converges rapidly. By setting appropriate parameters, our algorithm will converge to a NE after about 3-5 iterative operations which can satisfy the real-time requirement. The effect of the parameters (e.g. punishment factor, the constant factor c) on the performance is discussed. It is shown that the network throughput with our algorithm is 1 similar to 4 times greater than the traditional algorithm.