Collaborative spectrum sensing mechanism based on user incentive in cognitive radio networks

Abstract In cognitive radio networks (CRNs), it is important for secondary users (SUs) to efficiently reuse spectrum without interfering communication of primary users (PUs). To acquire the communication opportunities, SUs first need become winning, i.e., suppressing its own miss detection probability under the upper limit imposed by PUs. Collaborative spectrum sensing (CSS) is a promising approach to improve the detection performance of SUs, where multiple SUs form a group and share their sensing results. In addition, the probability that winning SUs correctly detect idle state of PUs’ spectrum will affect their communication opportunities. We first formulate a global optimization problem as integer linear programming (ILP), which maximizes both the number of winning SUs and total communication opportunities among them. In CSS, we also have to consider the selfishness of SUs because winning SUs will compete with group members to acquire their own communication opportunities. To cope with this competitive problem in addition to scalability problem of the global optimization, we further formulate an individual optimization problem, which can be solved by a user-incentive based CSS mechanism composed of PU selection and group (re)formation among SUs, where communication opportunities are allocated to SUs according to their detection performance. Through simulation experiments, we show the proposed mechanism considering selfishness of SUs is competitive with the existing scheme based on group-level cooperation, in terms of both the ratio of winning SUs and total communication opportunities among them. Comparing with the global optimization, we also show that the proposed mechanism can support larger-scale systems with performance improvement. In addition, we show that the proposed mechanism can achieve stable group formation even under SUs’ selfish behavior. Finally, we discuss how the number of PUs affects the system performance.

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