Cooperative spectrum sensing based on adaptive weighting for a cognitive radio system

We propose a combining scheme for hard decisions of secondary users to improve the performance of cooperative spectrum sensing in a cognitive radio system. In contrast to the conventional equal-weight combining, the proposed scheme assigns unequal weights to different users to form the global decision statistics. Specifically, the combining weights are updated adaptively such that a higher weight is given to the decision of a more reliable user. In order to update the weights, the fusion center estimates the reliability of each user based on the past recode of the user's local decisions. Numerical results show that the proposed scheme outperforms the equal-weight scheme and optimal scheme with counting method, especially when the channels from the primary transmitter to the secondary users are highly disparate.