Socially-optimal online spectrum auctions for secondary wireless communication

Abstract

Spectrum auctions are efficient mechanisms for licensed users to relinquish their under-utilized spectrum to secondary links for monetary remuneration. Truthfulness and social welfare maximization are two natural goals in such auctions, but cannot be achieved simultaneously with polynomial-time complexity by existing methods, even in a static network with fixed parameters. The challenge escalates in practical systems with QoS requirements and volatile traffic demands for secondary communication. Online, dynamic decisions are required for rate control, channel evaluation/bidding, and packet dropping at each secondary link, as well as for winner determination and pricing at the primary user. This work proposes an online spectrum auction framework with cross-layer decision making and randomized winner determination on the fly. The framework is truthful-in-expectation, and achieves close-to-offline-optimal time-averaged social welfare and individual utilities with polynomial time complexity. A new method is introduced for online channel evaluation in a stochastic setting. Simulation studies further verify the efficacy of the proposed auction in practical scenarios.