A clustering-based coordinated spectrum sensing in wideband large-scale cognitive radio networks

Efficient spectrum sensing is one of the key features that allows the implementation of fully agile cognitive radio networks. In this paper, we present an efficient coordinated spectrum sensing algorithm for wideband large-scale cognitive radio networks. Our approach is based on clustering secondary users according to their spectrum sensing results and performing the spectrum sensing tasks collaboratively within each cluster. In addition, the clusters can collaborate with each other to achieve an optimal distributed spectrum sensing across the network. We set up a cognitive radio framework and evaluate our proposed algorithm using numerical simulations. We show that the proposed algorithm increases the successful channel sensing rate at a reasonable computational cost.