Spectrum trading algorithm based on agent in cognitive radio networks

To design an efficient and effective cognitive radio networks, the related technical aspects and economic aspects need to be considered. This paper addresses the spectrum trading in cognitive radio networks, where there are multiple primary services (sellers), multiple secondary users (buyers) and one agent. In the system, multiple secondary users compete 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 this trading market. Simulation results showed that the proposed algorithm performs well.