Social Welfare Maximization Auction for Secondary Spectrum Markets: A Long-Term Perspective

Abstract

Dynamic secondary spectrum markets have gained tremendous attentions recently, which can provide significant flexibility for trading spectrum by conducting auctions periodically. The high price of spectrum necessitates a thorough consideration on secondary users' budget constraint, i.e. the total money they could pay. However, previous studies rarely deal with the practical issue of budget constraint, and concentrate on maximizing social welfare greedily in a single round auction, which may not guarantee their performance after multiple rounds of auctions. In this paper, we investigate the techniques for budget constrained periodic spectrum auction, which ensures approximate social welfare maximization from a long- term perspective. With the celebrated primal-dual method, we present a Periodic Spectrum Auction framework (PSA) that runs a tailored One Round Spectrum Auction (ORSA) in each round. In the ORSA, we achieve critical properties such as truthfulness, individual rationality and computational efficiency. Due to the dual fitting technique, ORSA not only achieves approximate social welfare maximization in one round, but also guarantees only a small loss of approximation ratio when runs in multiple rounds under the PSA framework. Finally, we conduct extensive simulations to demonstrate the performance of our schemes.