A General Framework for Wireless Spectrum Auctions

TLDR

Spectrum auctions must account for local demand and availability to maximize revenue and utilization. The authors propose a real‑time spectrum auction framework for distributing spectrum among many wireless users while respecting interference constraints. The framework employs a compact bidding language, multiple pricing models to balance revenue and fairness, and fast clearing algorithms to compute revenue‑maximizing prices and allocations in real time. Analytical and experimental results show that the framework yields conflict‑free, revenue‑maximizing, and utilization‑efficient allocations, and that bidding behavior and pricing models significantly influence outcomes.

Abstract

We propose a real-time spectrum auction framework to distribute spectrum among a large number wireless users under interference constraints. Our approach achieves conflict-free spectrum allocations that maximize auction revenue and spectrum utilization. Our design includes a compact and yet highly expressive bidding language, various pricing models to control tradeoffs between revenue and fairness, and fast auction clearing algorithms to compute revenue-maximizing prices and allocations. Both analytical and experimental results verify the efficiency of the proposed approach. We conclude that bidding behaviors and pricing models have significant impact on auction outcomes. A spectrum auction system must consider local demand and spectrum availability in order to maximize revenue and utilization.