In recent years, spectrum sharing has received much attention as a technique for more efficient spectrum use. In the case in which all providers are cooperative, spectrum sensing can easily be realized and can improve user throughput (on average). If that is not the case, providers are not cooperative, i.e., spectrum trading, spectrum bands are rented to promote spectrum sharing. To ensure more profit, however, non-cooperative providers must correctly estimate the fluctuation of the number of connected users to be able to determine the offered channel price. In this paper, we propose a spectrum sharing method to achieve both higher throughput and provider profit via appropriate pricing using a disaggregate behavioral model. Finally, we confirm the effectiveness of the proposed method using simulation experiments.

In this paper, we study the problem of distributed spectrum allocation under a vertical spectrum sharing scenario in a cognitive radio network. The secondary users share the spectrum licensed to the primary user by observing the activity statistics of the primary users, and regulate their transmission strategy in order to abide by the spectrum sharing etiquette. When the primary user is inactive in a subset of the available frequency bands, from the perspective of the secondary users the problem reduces to a distributed horizontal spectrum sharing. For a specific class of networks, the latter problem is addressed by the recently proposed GADIA algorithm [1]. In this paper, we present analytical and numerical results on the performance of the GADIA algorithm in conjunction with the above-mentioned vertical spectrum sharing scenario. These results reveal near-optimal performance guarantees for the overall vertical spectrum sharing scenario.

Most of previous works have presented the dynamic spectrum allocation (DSA) gain achieved by utilizing the time or regional variations in traffic demand between multi-network operators (NOs). In this paper, we introduce the functionalities required for the entities related with the spectrum sharing and allocation and propose a spectrum allocation algorithm while considering the long-term priority between NOs, the priority between multiple class services, and the urgent bandwidth request. To take into account the priorities among the NOs and the priorities of multiple class services, a spectrum sharing metric (SSM) is proposed, while a negotiation procedure is proposed to treat the urgent bandwidth request.