An Auction Approach to Resource Allocation in OFDM-Based Cognitive Radio Networks

We study a repeated auction for the resource allocation problem in OFDM-based cognitive radio networks (CRNs), in which secondary users (SUs) share the primary spectrum under the interference constraints of primary users (PUs). With the inter-cell interference and mutual interference between PUs and SUs, the resource allocation problem is formulated as a non-convex optimization problem. Auction performs well in solving non-convex problems, therefore the interference auction with cooperative bidding is proposed. Moreover, with the theoretical analysis of equilibrium, an implementation algorithm for the auction is developed and the convergence is proved. Simulation results show that the interference auction obtains a good spectrum efficiency improvement and a rapid convergence rate.