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In this paper, we propose a green spectrum and infrastructure leasing framework for sharing unused TV spectrum, in which the ownership of the network infrastructure and spectrum are decoupled, and each can be leased as a service on demand. An incumbent TV spectrum owner (TSO) can lease a share of the infrastructure from a network infrastructure owner (NIO) with a pay-per-use model, to provide new services to its end users. On the other hand, a TSO can rent a portion of its unused spectrum to the NIO for revenue such that the NIO can obtain access to the spectrum to serve its customers. This proposed framework achieves green communications through both resource sharing and energy saving. Our paper aims to analyze the interplay between TSO and NIO, and create a win–win situation to provide sufficient incentives for them to cooperate on this green communications. A multistage Stackelberg game is formulated, where TSO and NIO sequentially determine the total bandwidth supply for sharing, the infrastructure leasing price, the amount of infrastructure to lease, the spectrum leasing price, and the amount of spectrum to lease to maximize their utilities. The best strategies that will be taken by the TSO and NIO under various deployment scenarios are analyzed. Evaluation results show that the proposed green spectrum and infrastructure leasing framework is a promising scheme under which both TSO and NIO can benefit, and their utilities can be maximized in terms of user data throughput and revenue/payment, which provides sufficient incentives for them to cooperate. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the problem of cooperative spectrum sensing scheduling (C3S) in a cognitive radio network (CRN) when there exist multiple primary channels. Our work focuses on a scenario in which each secondary user (SU) has the freedom to decide whether to participate in cooperative spectrum sensing; if not, the SU becomes a free rider. Such a mechanism can conserve the energy for spectrum sensing at a risk of sacrificing the spectrum sensing performance. To overcome this problem, we address the following two questions: “Which action (contributing to spectrum sensing or not) should be taken?” and “which channel should be sensed?” We model our framework as an evolutionary game in which each SU makes its decision based on its utility history and takes an action more frequently if it brings a relatively higher utility. We also develop a coalition formation algorithm based on the channel status, where each SU always chooses the coalition that brings the most information regarding the status of the corresponding channel. The simulation results demonstrate that the proposed scheme can guarantee the detection probability at a low false alarm rate. The results also indicate that our algorithm can satisfy different requirements by carefully tuning the system parameters. [ABSTRACT FROM PUBLISHER]