Dynamic Spectrum Auction with Time Optimization in Cognitive Radio Networks

Abstract

Dynamic spectrum auction has been considered as one of potential approaches on spectrum allocation in cognitive radio networks. As an modified version of traditional static or quasi-static spectrum auction, dynamic spectrum auction should not only increase the auction revenue of the owner of spectrum, but also improve spectrum utilization on fine time granularity. We propose a dynamic spectrum auction algorithm with time optimization (DSA-TO) in 802.22 networks. First, the effects of auction period on auction revenue and spectrum utilization are argued and optimized. Then we give a complete spectrum auction procedure where an adaptive reservation price is used to balance the revenue and utilization of spectrum auction. Performance analyses show that the DSA-TO algorithm can resist collusion effectively and has low complexity as well as good revenue and utilization. Simulation results show that the DSA-TO algorithm is reasonable in the optimization of auction period and can keep a fine spectrum utilization and bring more revenue for both single unit spectrum auction and multi-unit spectrum auction.