In secondary spectrum trading markets, auctions are widely used by spectrum holders (SHs) to redistribute their unused channels to secondary wireless service providers (WSPs). As sellers, the SHs design proper auction schemes to stimulate more participants and maximize the revenue from the auction. As buyers, the WSPs determine the bidding strategies in the auction to better serve their end users. In this paper, we consider a three-layered spectrum trading market consisting of the SH, the WSPs and the end users. We jointly study the strategies of the three parties. The SH determines the auction scheme and spectrum supplies to optimize its revenue. The WSPs have flexible bidding strategies in terms of both demands and valuations considering the strategies of the end users. We design FlexAuc, a novel auction mechanism for this market to enable dynamic supplies and demands in the auction. We prove theoretically that FlexAuc not only maximizes the social welfare but also preserves other nice properties such as truthfulness and computational tractability.
Most of the state-of-the-art mechanisms assume that buyers can claim at most one channel. These mechanisms cannot satisfy the flexible demands from buyers. Single-seller multi-buyer auction with homogeneous channels has been studied extensively. VERITAS in @cite_13 allowed users to buy channels based on their demands and spectrum owner to maximize revenue with spectrum reuse. In @cite_3 the authors proposed a VCG auction to maximize the expected revenue of the seller and a suboptimal auction to reduce the complexity for practical purpose. Double auction mechanisms are studied for the multi-seller multi-buyer case. McAfee mechanism @cite_0 was proposed for trading homogeneous items in double auction. Many follow-up works has been done since then @cite_14 @cite_18 @cite_16 @cite_10 .
@cite_18 @cite_14 @cite_10 @cite_3 @cite_0 @cite_16 @cite_13
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Spectrum is a critical yet scarce resource and it has been shown that dynamic spectrum access can significantly improve spectrum utilization. To achieve this, it is important to incentivize the primary license holders to open up their under-utilized spectrum for sharing. In this paper we present a secondary spectrum market where a primary license holder can sell access to its unused or under-used spectrum resources in the form of certain fine-grained spectrum-space-time unit. Secondary wireless service providers can purchase such contracts to deploy new service, enhance their existing service, or deploy ad hoc service to meet flash crowds demand. Within the context of this market, we investigate how to use auction mechanisms to allocate and price spectrum resources so that the primary license holder's revenue is maximized. We begin by classifying a number of alternative auction formats in terms of spectrum demand. We then study a specific auction format where secondary wireless service providers have demands for fixed locations (cells). We propose an optimal auction based on the concept of virtual valuation. Assuming the knowledge of valuation distributions, the optimal auction uses the Vickrey-Clarke-Groves (VCG) mechanism to maximize the expected revenue while enforcing truthfulness. To reduce the computational complexity, we further design a truthful suboptimal auction with polynomial time complexity. It uses a monotone allocation and critical value payment to enforce truthfulness. Simulation results show that this suboptimal auction can generate stable expected revenue. We propose a mechanism for auctioning bundles of multiple divisible goods. Such a mechanism is very useful for allocation of bandwidth in a network where the buyers want the same amount of bandwidth on each link in their route. We first propose a single-sided VCG-type mechanism. However, instead of reporting types, the players only reveal a two-dimensional bid signal - the maximum quantity that they want and the per unit price they are willing to pay. We show the existence of an efficient Nash equilibrium in the corresponding auction game of the mechanism. We show through an example that not all Nash equilibria are efficient but provide a distributed algorithm that yields the efficient one. Further, we provide a sufficient characterization of all efficient Nash equilibria. We then present a double-sided auction mechanism for multiple divisible goods, and show that there exists a Nash equilibrium of the auction game which yields the efficient allocation. We design truthful double spectrum auctions where multiple parties can trade spectrum based on their individual needs. Open, market-based spectrum trading motivates existing spectrum owners (as sellers) to lease their selected idle spectrum to new spectrum users, and provides new users (as buyers) the spectrum they desperately need. The most significant challenge is how to make the auction economic-robust (truthful in particular) while enabling spectrum reuse to improve spectrum utilization. Unfortunately, existing designs either do not consider spectrum reuse or become untruthful when applied to double spectrum auctions. We address this challenge by proposing TRUST, a general framework for truthful double spectrum auctions. TRUST takes as input any reusability-driven spectrum allocation algorithm, and applies a novel winner determination and pricing mechanism to achieve truthfulness and other economic properties while significantly improving spectrum utilization. To our best knowledge, TRUST is the first solution for truthful double spectrum auctions that enable spectrum reuse. Our results show that economic factors introduce a tradeoff between spectrum efficiency and economic robustness. TRUST makes an important contribution on enabling spectrum reuse to minimize such tradeoff. Revenue maximization in multi-item settings is notoriously elusive. This paper studies a class of two-item auctions which we call a mixed-bundling auction with reserve prices (MBARP). It calls VCG on an enlarged set of agents by adding the seller---who has reserve valuations for each bundle of items---and a fake agent who receives nothing nor has valuations for any item or bundle, but has a valuation for pure bundling allocations, i.e., allocations where the two items are allocated to a single agent. This is a strict subclass of several known classes of auctions, including the affine maximizer auction (AMA), λ-aution, and the virtual valuations combinatorial auction (VVCA). As we show, a striking feature of MBARP is that its revenue can be represented in a simple closed form as a function of the parameters. Thus, we can solve first-order conditions on the parameters and obtain the optimal MBARP. The optimal MBARP yields significantly higher revenue than prior auctions for which the revenue-maximizing parameters could be solved for in closed form: separate Myerson auctions, pure-bundling Myerson auction, VCG, and mixed-bundling auction without reserve prices. Its revenue even exceeds that obtained via simulation within broader classes: VVCA and AMA.