Summary: Towards Real-Time Dynamic Spectrum Auctions
Sorabh Gandhi, Chiranjeeb Buragohain*, Lili Cao, Haitao Zheng, Subhash Suri
Department of Computer Science
University of California, Santa Barbara, CA 93106 U.S.A
*Amazon.com, Seattle, WA 98106 U.S.A
Main contact: Haitao Zheng, firstname.lastname@example.org
In this paper, we propose a low-complexity auction framework to distribute spectrum in real-time among a large
number of wireless users with dynamic traffic. Our design consists of a compact and highly-expressive bidding
format, two pricing models to control tradeoffs between revenue and fairness, and fast auction clearing algorithms to
achieve conflict-free spectrum allocations that maximize auction revenue. We develop analytical bounds on algorithm
performance and complexity to verify the efficiency of the proposed approach. We also use both simulated and real
deployment traces to evaluate the auction framework. We conclude that pricing models and bidding behaviors have
significant impact on auction outcomes and spectrum utilization. Any efficient spectrum auction system must consider
demand and spectrum availability in local regions to maximize system-wide revenue and spectrum utilization.
Keywords: Auctions, Spectrum, Algorithms.
Reliable and efficient spectrum access is vital for
the growth and innovation of wireless technologies.
Unfortunately, historical (and current) spectrum