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Revenue-maximizing and truthful online auctions for dynamic spectrum access

机译:用于动态频谱访问的收入最大化和真实的在线拍卖

摘要

Secondary spectrum auctions have been suggested as a strategically robust mechanism for distributing idle spectrum to competing secondary users. However, previous work on such auction design have assumed a static auction setting, thus failing to fully exploit the inherently time-varying nature of spectrum demand and utilization. In this paper, we address this issue from the perspective of the primary user who wishes to maximize the auction revenue. We present an online auction framework that dynamically accepts bids and allocates spectrum. We prove rigorously that our online auction framework is truthful in the multiple dimensions of bid values, as well as bid timing parameters. To protect against unbounded loss of revenue due to latter bids, we introduce controlled preemption into our mechanism. We prove that preemption, coupled with the technique of inflating bids artificially, leads to an online auction that guarantees a 1 5 –fraction of the optimal revenue as obtained by an offline adversary. Since the previous guarantee holds only for the optimal channel allocation, we further provide a greedy channel allocation scheme which provides scalability. We prove that the greedy scheme also obtains a constant competitive revenue guarantee, where the constant depends on the parameter of the conflict graph.
机译:已经建议将二级频谱拍卖作为用于将空闲频谱分配给竞争的二级用户的战略上健壮的机制。但是,以前有关这种拍卖设计的工作假设是静态拍卖设置,因此无法充分利用频谱需求和利用的固有时变性质。在本文中,我们从希望最大化拍卖收入的主要用户的角度解决了这个问题。我们提出了一个在线拍卖框架,该框架可以动态接受出价并分配频谱。我们严格证明,我们的在线拍卖框架在出价值和出价时间参数的多个维度上都是真实的。为了防止由于后来的出价而造成的无限收入损失,我们将受控制的优先权引入了我们的机制。我们证明先发制人,再加上人为地提高出价的技术,导致了在线拍卖,该拍卖保证了线下对手获得的最佳收益的1 5-分数。由于先前的保证仅适用于最佳信道分配,因此我们进一步提供了一种可扩展的贪婪信道分配方案。我们证明了贪心方案也获得了一个恒定的竞争收入保证,该常数取决于冲突图的参数。

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