Revenue generation for truthful spectrum auction in dynamic spectrum access

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 spectrumspace-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

ECONOMIC APPROACHES AND MARKET STRUCTURES FOR TEMPORAL-SPATIAL SPECTRUM SHARING

In wireless communication systems, economic approaches can be applied to spectrum sharing and enhance spectrum utilization. In this research, we develop a model where geographic information, including licensed areas of primary users (PUs) and locations of secondary users (SUs), plays an important role in the spectrum sharing system. We consider a multi-price policy and the pricing power of noncooperative PUs in multiple geographic areas. Meanwhile, the value assessment of a channel is price-related and the demand from the SUs is price-elastic. By applying an evolutionary procedure, we prove the existence and uniqueness of the optimal payoff for each PU selling channels without reserve. In the scenario of selling channels with reserve, we predict the channel prices for the PUs leading to the optimal supplies of the PUs and hence the optimal payoffs. To increase spectrum utilization, the scenario of spatial spectrum reuse is considered. We consider maximizing social welfare via on-demand channel allocation, which describes the overall satisfaction of the SUs when we involve the supply and demand relationship. We design a receiver-centric spectrum reuse mechanism, in which the optimal channel allocation that maximizes social welfare can be achieved by the Vickrey-Clarke-Groves (VCG) auction for maximal independent groups (MIGs). We prove that truthful bidding is the optimal strategy for the SUs, even though the SUs do not participate in the VCG auction for MIGs directly. Therefore, the MIGs are bidding truthfully and the requirement for social welfare maximization is satisfied. To further improve user satisfaction, user characteristics that enable heterogeneous channel valuations need to be considered in spatial spectrum reuse. We design a channel transaction mechanism for non-symmetric networks and maximize user satisfaction in consideration of multi-level flexible channel valuations of the SUs. Specifically, we introduce a constrained VCG auction. To facilitate the bid formation, we transform the constrained VCG auction to a step-by-step decision process. Meanwhile, the SUs in a coalition play a coalitional game with transferable utilities. We use the Shapley value to realize fair payoff distribution among the SUs in a coalition

Resource Allocation and Pricing in Secondary Dynamic Spectrum Access Networks

The paradigm shift from static spectrum allocation to a dynamic one has opened many challenges that need to be addressed for the true vision of Dynamic Spectrum Access (DSA) to materialize. This dissertation proposes novel solutions that include: spectrum allocation, routing, and scheduling in DSA networks. First, we propose an auction-based spectrum allocation scheme in a multi-channel environment where secondary users (SUs) bid to buy channels from primary users (PUs) based on the signal to interference and noise ratio (SINR). The channels are allocated such that i) the SUs get their preferred channels, ii) channels are re-used, and iii) there is no interference. Then, we propose a double auction-based spectrum allocation technique by considering multiple bids from SUs and heterogeneity of channels. We use virtual grouping of conflict-free buyers to transform multi-unit bids to single-unit bids. For routing, we propose a market-based model where the PUs determine the optimal price based on the demand for bandwidth by the SUs. Routes are determined through a series of price evaluations between message senders and forwarders. Also, we consider auction-based routing for two cases where buyers can bid for only one channel or they could bid for a combination of non-substitutable channels. For a centralized DSA, we propose two scheduling algorithms-- the first one focuses on maximizing the throughput and the second one focuses on fairness. We extend the scheduling algorithms to multi-channel environment. Expected throughput for every channel is computed by modelling channel state transitions using a discrete-time Markov chain. The state transition probabilities are calculated which occur at the frame/slot boundaries. All proposed algorithms are validated using simulation experiments with different network settings and their performance are studied

Negotiable Auction Based on Mixed Graph: A Novel Spectrum Sharing Framework

© 2015 IEEE. Auction-based spectrum sharing is a promising solution to improve the spectrum utilization in 5G networks. Along with the spatial reuse, we observe that the ability to adjust the coverage of a spectrum bidder can provide room to itself for further negotiation while auctioning. In this paper, we propose a novel economic tool, size-negotiable auction mechanism (SNAM), which provides a hybrid solution between auction and negotiation for multi-buyers sharing spectrum chunks from a common database. Unlike existing auction-based spectrum sharing models, each bidder of the SNAM submits its bid for using the spectrum per unit space and a set of coverage ranges over which the bidder is willing to pay for the spectrum. The auctioneer then coordinates the interference areas (or coverage negotiation) to ensure no two winners interfere with each other while aiming to maximize the auction's total coverage area or revenue. In this scenario, the undirected graph used by existing auction mechanisms fails to model the interference among bidders. Instead, we construct a mixed interference graph and prove that SNAM's auctioning on the mixed graph is truthful and individually rational. Simulation results show that, compared with existing auction approaches, the proposed SNAM dramatically improves the spatial efficiency, hence leads to significantly higher seller revenue and buyer satisfaction under various setups. Thanks to its low complexity and low overhead, SNAM can target fine timescale trading (in minutes or hours) with a large number of bidders and requested coverages