Constant false alarm energy detection based on Markov transfer characteristics in cognitive radio

Cognitive Radio is an emerging technology to improve the utilization of licensed spectrum. Spectrum sensing is one of the key tasks for cognitive radio. Previous research on spectrum sensing has not fully investigated the characteristics of the primary user. This paper analyzes the Markov transfer characteristics of the primary user, based on which the current state of the primary user is predicted to adjust the decision threshold and improve detection accuracy. Firstly, we illustrate the Markov transfer characteristics of the primary user. Secondly, we illustrate benefits of the characteristics and derive the upper bound of the detection probability we can achieve. Finally, we introduce a new algorithm to exploit the Markov transfer characteristics. Simulation results are given to verify the performance of the proposed algorithm in this paper.