Auction Based Spectrum Trading for Cognitive Radio Networks

In this letter, we consider the shared used model in cognitive radio networks and design a spectrum trading method to maximize the total satisfaction of the Secondary Users (SUs) and revenue of the Wireless Service Provider (WSP). In our design, we consider the risk of imperfect spectrum sensing which causes the SUs miss the presence of licensed users and interfere with them. Taking into account this risk, we first propose a multi-unit sequential sealed-bid first-price auction to optimize the payoff of each SU. Then, we derive an expression for the total revenue of WSP and maximize it by optimizing the sensing time. Our results demonstrate that the proposed auction-based spectrum trading method brings better revenue than its counterparts.