Robust hard decision combination scheme based on Kullback-Leibler divergence for cooperative spectrum sensing in cognitive radio

Cognitive radio (CR) network is a new, emerging research area because it has the ability to improve spectrum utilization by detecting and using vacant channels that are unused by licensed users. Reliable detection of the licensed user signal is a prerequisite for CR network to avoid interference to the licensed user. Cooperative spectrum sensing (CSS) is able to offer better sensing performance in comparison with individual sensing. However, CSS is vulnerable to attack from malicious users who falsify sensing data. In this paper, we propose a robust hard decision combination rule based on the KullbackLeibler divergence (KL divergence) for CSS. The proposed scheme can achieve sensing performance similar to that of the optimal hard decision combination rule, the ChairVarshney rule, while not requiring information on the signal-to-noise ratio. Furthermore, the proposed scheme can provide secure CSS against some common types of malicious users without any user identification step. Our simulation results prove the effectiveness of the proposed scheme. (c) 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.