Auction-based spectrum sharing
Mobile Networks and Applications
Spectrum auction framework for access allocation in cognitive radio networks
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
Multi-Stage Pricing Game for Collusion-Resistant Dynamic Spectrum Allocation
IEEE Journal on Selected Areas in Communications
A highly available spectrum allocation service model in dynamic spectrum market
Future Generation Computer Systems
International Journal of Communication Systems
WASA'13 Proceedings of the 8th international conference on Wireless Algorithms, Systems, and Applications
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Extensive research in recent years has shown the benefits of cognitive radio technologies to improve the flexibility and efficiency of spectrum utilization. This new communication paradigm, however, requires a well-designed spectrum allocation mechanism. In this paper, we propose an auction framework for cognitive radio networks to allow unlicensed secondary users (SUs) to share the available spectrum of licensed primary users (PUs) fairly and efficiently, subject to the interference temperature constraint at each PU. To study the competition among SUs, we formulate a non-cooperative multiple-PU multiple-SU auction game and study the structure of the resulting equilibrium by solving a non-continuous two-dimensional optimization problem. A distributed algorithm is developed in which each SU updates its strategy based on local information to converge to the equilibrium. We then extend the proposed auction framework to the more challenging scenario with free spectrum bands. We develop an algorithm based on the no-regret learning to reach a correlated equilibrium of the auction game. The proposed algorithm, which can be implemented distributedly based on local observation, is especially suited in decentralized adaptive learning environments as cognitive radio networks. Finally, through numerical experiments, we demonstrate the effectiveness of the proposed auction framework in achieving high efficiency and fairness in spectrum allocation.