首页|Optimal linear weighted cooperative spectrum sensing for clustered-based cognitive radio networks
Optimal linear weighted cooperative spectrum sensing for clustered-based cognitive radio networks
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Springer Nature
Abstract The lack of spectrum resources restricts the development of wireless communication applications. In order to solve the problems of low spectrum utilization and channel congestion caused by the static division of spectrum resource, this paper proposes an optimal linear weighted cooperative spectrum sensing for clustered-based cognitive radio networks. In this scheme, different weight values will be assigned for cooperative nodes according to the SNR of cognitive users and the historical sensing accuracy. In addition, the cognitive users can be clustered, and the users with the better channel characteristics will be selected as cluster heads for gathering the local sensing information. Simulation results show that the proposed scheme can obtain better sensing performance, improve the detection probability and reduce the error probability.
Linear weighted fusionCooperative spectrum sensingSignal-to-noise ratioCognitive radio networksFusion center
NSTL
Springer Nature
