Dynamic Spectrum Auction Research Articles

Dynamic Fairness-Aware Spectrum Auction for Enhanced Licensed Shared Access in UAV-based Networks

Dynamic Fairness-Aware Spectrum Auction for Enhanced Licensed Shared Access in UAV-based Networks

Robust Large-Scale Spectrum Auctions against False-Name Bids

Auction is a promising approach for dynamic spectrum access in cognitive radio networks. Existing auction mechanisms are mainly strategy-proof to stimulate bidders to reveal their valuations of spectrum truthfully. However, they can suffer significantly from a new cheating pattern, named false-name bids, where a bidder can manipulate the auction by submitting bids under multiple fictitious names. We show such false-name bid cheating is easy to make but difficult to detect in dynamic spectrum auctions. To address this issue, we propose ALETHEIA, a novel flexible, false-name-proof auction framework for large-scale dynamic spectrum access. ALETHEIA not only guarantees strategy-proofness but also resists false-name bids. Moreover, ALETHEIA enables spectrum reuse across a large number of bidders, to improve spectrum utilization. Following that, we extend ALETHEIA to its general version that supports more practical and flexible auction, where bidders accept the spectrum allocation under their partial satisfactions. Theoretical analysis and simulation results show that ALETHEIA achieves both high spectrum redistribution efficiency and auction efficiency.

LYRIC: Local Recall-Based Dynamic Double Spectrum Auction Mechanism With Heterogeneous-Demand Secondary Users

In this paper, we investigate the problem of recall mechanism in a dynamic spectrum auction system. The licensed spectrum holders (SHs) can auction their idle channels to the secondary wireless service providers (SWSPs) for economic incentive. However, the primary user (PU) of an SH has higher priority than the SWSPs for the spectrum access. To deal with a sudden increase in PUs’ spectrum demands after auction and guarantee their quality of services (QoS), we propose a Local recall-based dYnamic double spectRum auctIon meChanism (LYRIC) for SHs’ spectrum auction operation. Different from the most existing approaches about spectrum recall-based spectrum auction, the proposed spectrum auction method for heterogeneous spectrum transaction takes account of the joint effect of heterogeneous demand , spectrum spatial reusability , and the economic efficiency . Simulation results show that the proposed LYRIC algorithm can improve the auction process of SHs, the channels utilization efficiency and the average buyers’ satisfactory level with guarantees on the QoS of PUs.

Truthful Auctions for Continuous Spectrum with Variable Bandwidths

Dynamic spectrum auctions have been considered a promising approach to effectively re-distribute spectrum resources in the secondary spectrum market. However, the existing spectrum auctions are limited to allocating spectrum in units of channels. Recently software defined radio technologies make exciting progress in operating radios with variable bandwidths. They push the need for designing more flexible spectrum auction frameworks that allow to allocate spectrum with variable bandwidth to the secondary user. In this paper, we design truthful spectrum auction frameworks in which secondary users can bid for, and then be actually allocated spectra with variable bandwidths. We first present a truthful framework for auctions of variable-bandwidth spectra in single collision domains, which can achieve system efficiency. Then, we propose a similar framework for multiple collision domains and rigorously show that it is also truthful. Results of extensive evaluations demonstrate that both of our spectrum auction frameworks for variable bandwidth are effective.

Profit maximization for secondary users in dynamic spectrum auction of cognitive radio networks

AbstractAs a powerful economic theory, auction mechanism has been extensively studied in dynamic spectrum allocation for cognitive radio networks (CRNs) recently. Different from most of existing works that focused on the mechanism design from the spectrum owner's side, we study from a new perspective on profit maximization of the secondary users (SUs). Because the spectrum auction mechanism has already been designed by the spectrum owner, we derive SUs' optimal bid strategies, which maximize their profits. First, we relax the limitation of SU's value on spectrum band, which is formerly defined as the transmission rate on channel, and introduce the affiliated value considering the impacts from other SUs. Further, the optimal value determination function is derived, which maximizes SU's expected profit; second, we analyze the auctioneer cheating issue, which has great influence on SU's profit, and the Nash equilibrium strategies for both spectrum owner and SUs are derived. Moreover, the repeated auction game mechanism is proposed that resists the auctioneer cheating effectively. Copyright © 2013 John Wiley & Sons, Ltd.

Recall-Based Dynamic Spectrum Auction with the Protection of Primary Users

Dynamic spectrum auction is considered as an effective solution to improve spectrum utilization efficiency in dynamic spectrum sharing networks because it can provide an economic incentive to motivate primary users to share their idle spectrum with secondary users. However, the primary users' own quality of services (QoS) cannot be guaranteed in case of demand peak because their spectrum is being used by the winners at auction. To solve this problem, we propose a recall-based dynamic spectrum auction (RBDSA) algorithm with which a primary base station (PBS) can auction its unused channels to some secondary wireless services providers (SWSPs) safely and economically. The PBS' users are granted a higher channel access priority than the SWSPs, then the PBS can recall some channels after auction to satisfy its demand if necessary. To maximize its profit from spectrum auction and self services, the PBS will reduce its excessive or deficient channels reservation, which is enforced with an introduction of punishment item in the PBS' utility. We show analytically that both the PBS and the SWSPs in the RBDSA algorithm are truthful and there is a weakly dominant equilibrium. Moreover, it can be extended to the scenarios with multiple units of channels demand and multiple PBSs. Simulation results show that the RBDSA algorithm can increase the utility of the PBS and improve the channels utilization efficiency while keeping the QoS of the primary users.

A DOF‐based dynamic spectrum auction algorithm in cognitive femtocell

SUMMARYDynamic spectrum auction (DSA) has been considered as one of potential spectrum allocation approaches in cognitive femtocell networks. As a modified version of traditional spectrum auction, DSA should not only increase auction revenue but also improve spectrum utilization on finer time granularity. We propose a DSA algorithm based on a double optimization framework (DOF), which focuses on the optimization of auction revenue and spectrum utilization. The optimization processing consists of two stages. Firstly, a proper auction period is selected to balance the expected spectrum utilization and auction revenue. Then, the cognitive femtocell base station adjusts its reserve price with the repetition of auction to leverage over instant revenue and spectrum utilization. At the same time, the bidders can adjust their bidding price to improve utilities. Performance analysis shows that the DOF‐based DSA algorithm has low complexity and can resist collusion, so it can be carried out frequently with small overhead. On the other hand, it is better than the greedy algorithm and Vickrey–Clarke–Groves auction on revenue. Simulation results show that the DOF‐based DSA algorithm can keep a fine spectrum utilization and bring the cognitive femtocell base station more revenue in both single‐unit award spectrum auction and multi‐unit awards spectrum auction. Copyright © 2012 John Wiley & Sons, Ltd.

Dynamic Spectrum Auction and Load Balancing Algorithm in Heterogeneous Network

Mobile communication plays an important role in the future of communication systems. To meet personalized and intelligent requirements, mobile communication has evolved from single wireless cellular network to heterogeneous mobile communication network, including wireless cellular network, wireless local network, and wireless personal network. In the heterogeneous communication system, to entirely fulfill the spectrum resource complementary advantages of such a heterogeneous wireless network, the spectrum resource trade algorithm has attracted tremendous research efforts. In this paper, the advantages and disadvantages of dynamic spectrum allocation and load balancing are discussed and spectrum auction takes the place of spectrum allocation to maximize the operation revenue. The authors design a joint spectrum auction and load balancing algorithm (SALB) based on heterogeneous network environment to develop a more flexible and efficient spectrum management. The simulation result shows that SALB increases the operation profit significantly.

Towards real-time dynamic spectrum auctions

In this paper, we propose a low-complexity auction framework to distribute spectrum in real-time among a large number of wireless users with dynamic traffic. Our design consists of a compact and highly expressive bidding format, two pricing models to control tradeoffs between revenue and fairness, and fast auction clearing algorithms to achieve conflict-free spectrum allocations that maximize auction revenue. We develop analytical bounds on algorithm performance and complexity to verify the efficiency of the proposed approach. We also use both simulated and real deployment traces to evaluate the auction framework. We conclude that pricing models and bidding behaviors have significant impact on auction outcomes and spectrum utilization. Any efficient spectrum auction system must consider demand and spectrum availability in local regions to maximize system-wide revenue and spectrum utilization.