Improvement of Auctioneer's Revenue under Incomplete Information in Cognitive Radio Networks

Abstract

In this letter, the problem of how to set reserve prices so as to improve the primary user's revenue in the second price-sealed auction under the incomplete information of secondary users' private value functions is investigated. Dirichlet process is used to predict the next highest bid based on historical data of the highest bids. Before the beginning of the next auction round, the primary user can obtain a reserve price by maximizing the additional expected reward. Simulation results show that the proposed scheme can achieve an improvement of the primary user's averaged revenue compared with several counterparts.