Localization algorithm of energy efficient radio spectrum sensing in cognitive internet of things radio networks

Spectrum sensing is a key problem of implementing cognitive radio (CR). Some malicious users falsify data, which reduces the performance of spectrum sensing. To this end, trustful cluster-based cooperative compressed spectrum sensing (TCBCSS) algorithm is proposed orienting to malicious user environment. Maximum likelihood (ML) is firstly used for estimating the distance from the cluster to the primary user, and the distance is compared with the preset threshold value so as to seek for the trustful cluster. Then, the channel condition is detected using the compressed spectrum sensing algorithm according to the information provided by the trustful cluster. The simulation result indicates that the proposed TCBCSS algorithm could cope with the malicious user environment effectively, detect the malicious user accurately, and maintain high spectrum detection rate.