Cluster-based Cooperative Spectrum Sensing in two-layer hierarchical Cognitive Radio Networks

The paper investigates cluster-based Cooperative Spectrum Sensing (CSS) issues in two-layer hierarchical Cognitive Radio Networks (CRNs). Most previous studies focus on hard decision fusion under the assumption of perfect reporting channels. However, wireless channels are not error-free in reality. Therefore, we propose a novel cluster-based CSS scheme with imperfect reporting channels between SUs and cluster heads (CHs) to optimize cluster strategy. A weighted reporting channel method is adopted in our analysis. To further reduce the complexity, 1^st order Taylor series expansion approximation scheme is proposed. Numerical results show that the proposed scheme achieves a satisfying performance.