A weighted cooperative spectrum sensing in cognitive radio networks
Lin Xiao, Kai Liu, Lin Ma · 2010
In cognitive radio networks (CRNs), different received signal-to-noise ratios (SNRs) of secondary users (SUs) lead to different reliability of their local spectrum sensing decisions, and then greatly affect sensing capability of cooperative spectrum sensing. Cooperative spectrum sensing with traditional hard decisions can not improve sensing capability efficiently due to allocating the same weight to SUs' decisions. Therefore, a weighted cooperative spectrum sensing (WCSS) is proposed for CRNs to improve sensing capability. It obtains weights of SUs' decisions from their average received SNRs, integrates both their independent decisions and weights to fuse data, and makes a final sensing decision. Simulation results show that compared to cooperative spectrum sensing with traditional hard decisions, WCSS performs better at low SNR.