Location-Oriented Evolutionary Games for Spectrum Sharing

Spectrum sharing between primary users (PUs) and secondary users (SUs) can be realized using economic approaches. In this paper, we propose a method for multiple PUs to share with multiple SUs different idle channels in overlapped licensed areas. Due to the fluctuations of supply and demand in different areas, the SUs are grouped according to their suppliers and the PUs set channel transaction quotas for these SU groups. By applying evolutionary games, the PUs can obtain quotas of evolutionary stable strategy (ESS) and achieve their maximum payoffs theoretically. Furthermore, we design a learning process for the PUs to attain best integer quotas that are realizable. In our simulation, we obtain under two pricing schemes both ESS and best integer quotas that render payoffs close to each other.