Distributed Spectrum Sensing for Cognitive Radio Sensor Networks using Diffusion Adaptation
Amirhosein Hajihoseini, Seyed Ali Ghorashi
Cognitive radio is a practical solution for spectrum scarcity. In cognitive networks, unlicensed (secondary) users should sense the spectrum before any usage, to make sure that the licensed (primary) users do not use the spectrum at that time. Due to the importance of spectrum sensing in cognitive networks, this should be fast and reliable, particularly in networks with communication link failure, which leads to network topology change. Decentralized decision making algorithms are known as a promising technique to provide reliability, scalability and adaptation, especially in sensor networks. In this paper, we propose a distributed diffusion based method in which, secondary users (sensors) cooperate to improve the performance of spectrum sensing. The proposed method provides a significant improvement in convergence rate and reliability. Simulation results indicate that the proposed algorithm shows an acceptable performance and converges twice faster than recently proposed consensus based spectrum sensing algorithms in the literature, and is almost insensitive to communication link failure.