A Stochastic Spectrum Trading and Resource Allocation Framework for Opportunistic Dynamic Spectrum Access Networks

Abstract

In this article, the spectrum trading problem between primary users and secondary networks is investigated. The secondary network requests multiple channels with the targeted availability to satisfy its users' demands. Due to the uncertainty about the channels availability, stochastic optimization techniques are adopted to find the optimal set of channels for each secondary network for the lowest cost. Two different constraints on the secondary demand are defined. The first one is when the throughput has to be fully satisfied for a certain percentage of time, and the second one is when the expected value of the throughput has to exceed a certain percentage of the requested one. Also, the possibility for channel subleasing among the secondary networks is investigated to reduce the demand shortage. The results show that demanding simultaneous channels increases the cost as it reaches up to 20% higher than if the same resources were requested individually. Also, channels subleasing reduces the demand shortage probability and increases the achieved throughput, especially at low value of requested demand. In this case, the demand satisfaction probability increases by around 30% while the achieved throughput increases up to 40% compared to the scenario where channels subleasing is not allowed.