A spectrum trading algorithm using an agent in cognitive radio networks

To design an efficient and efficient cognitive radio networks, the related technical and economic aspects should be needed to be considered. In this paper, an effective algorithm is proposed to address the spectrum trading in cognitive radio networks where there are multiple primary services (sellers), multiple secondary users (buyers) and one agent. In the algorithm, every secondary user competes with each other in terms of the spectrum demand quantity for the agent. And then, Nash equilibrium is used as the solution of the game. When the agent gets the information of total spectrum demand quantity, it buys spectrum from the sellers according to their prices. Each seller dynamically adjusts the price according to its supply function and the spectrum demand of the agent. Market-Equilibrium price is considered as the optimal solution where there is no excess spectrum in the trading market. Simulation results showed that the proposed algorithm is effective.