Research Article
An Agent-based Model of the Risk-based Spectrum Auction in the Cognitive Radio Networks
@INPROCEEDINGS{10.4108/icst.5gu.2014.257843, author={J\^{a}n Pastirč\^{a}k and Luk\^{a}š Sendrei and Stanislav Marchevsk\"{y} and Juraj Gazda}, title={An Agent-based Model of the Risk-based Spectrum Auction in the Cognitive Radio Networks}, proceedings={1st International Conference on 5G for Ubiquitous Connectivity}, publisher={IEEE}, proceedings_a={5GU}, year={2014}, month={12}, keywords={spectrum trading imperfect sensing agent-based modeling}, doi={10.4108/icst.5gu.2014.257843} }- Ján Pastirčák
Lukáš Sendrei
Stanislav Marchevský
Juraj Gazda
Year: 2014
An Agent-based Model of the Risk-based Spectrum Auction in the Cognitive Radio Networks
5GU
IEEE
DOI: 10.4108/icst.5gu.2014.257843
Abstract
In this paper, we propose an agent-based model for spectrum trading in the shared use model of dynamic spectrum access. Spectrum trading is employed using the single-unit sealedbid first-price auction, which takes into the account risk caused by the imperfect spectrum sensing. Bidding strategies of the bidder are controlled by the reinforcement learning algorithm. Cooperative energy-based spectrum sensing is used as a spectrum sensing mechanism. Two different decision fusion strategies, which provide different levels of risk are discussed. The results demonstrate that in risky environment, total revenue and total payoff of the auctioneer and bidder respectively is higher, than in the case of system with lower level of risk. On the other hand, normalized revenue and payoff per a single auction round is higher in the case with lower level of risk. Moreover, the results have shown that the optimum sensing time for maximizing revenue and payoff is different.
