Robust threshold design for cooperative sensing in cognitive radio networks

The successful coexistence of cognitive radio systems and licensed systems requires the secondary users to have the capability of sensing and keeping track of primary transmissions. While existing spectrum sensing methods usually assume known distributions of the primary signals, such an assumption is often not true in practice. As a result, applying existing sensing methods directly will often lead to unreliable detection performance in practical networks. In this paper, we try to improve the sensing performance under the distribution uncertainty of primary signals. We formulate the optimal sensing design as a robust optimization problem, and propose an iterative algorithm to determine the optimal decision threshold for each user. Extensive simulations demonstrate the effectiveness of our proposed algorithm.