Dynamic power control algorithm and simulation in cognitive radio system

In cognitive radio system, power control is a key technique to copes with near-far effect, reduce multiple access interference and increase capacity of communication. Considering utility function can not be dynamic adjusted to the current utilization of system resources, this paper combines the real environment of wireless communication and proposes an optimized power control algorithm which particularly concerns about the price function should be changed with the congestion of the system. This paper proves the existence of Nash equilibrium, uniqueness and convergence about the utility function. Simulation result shows that the game theory with the dynamic price function can improve performance in term of balancing between increasing utility and decreasing power consumption of terminal.