Collaborative Spectrum Sensing Mechanism Based on User Incentive in Cognitive Radio Networks

Tomohiro Nishida (1651083)


Cognitive radio networks have been expected to improve the spectrum utilization by allowing unlicensed users, called secondary users (SUs), to use the idle spectrum of licensed users, called primary users (PUs). Since the interference in PU's communications should be minimized, collaborative spectrum sensing (CSS) by multiple SUs has been proposed to improve the detection performance of SUs to the signal of PU. After SUs conduct CSS, each SU individually aims to use the idle spectrum, which is a kind of competitive situations. In this thesis, we propose a CSS mechanism based on user incentive for multi-PU cognitive radio networks. In the proposed mechanism, communication opportunities are allocated to SUs according to their detection performance. We first formulate the group formation as an optimization problem where each SU aims to maximize its own communication opportunities under a constraint on the upper limit of miss detection probability, by selecting an appropriate PU and forming a group with appropriate SUs. We also propose a selfish group reformation scheme where each SU aims to improve its own communication opportunities by reforming the group. Through several simulation experiments, we show that the proposed mechanism can increase the ratio of winning SUs, which meet the constraint on miss detection probability and acquire the communication opportunities, compared to the existing scheme. We also demonstrate that introducing the user incentive contributes to not only allocating the communication opportunities to SUs according to their detection performance but also improving the ratio of winning SUs with low detection performance. Finally, we also show that the proposed mechanism can achieve stable group formation even under SUs' selfish behavior.