An HMM-based spectrum access algorithm for cognitive radio systems

In this paper, we propose an improved spectrum access algorithm for cognitive radio applications using a Hidden Markov Model (HMM) for learning the primary user channel usage pattern. The proposed scheme maximizes the channel utilization without causing significant interference to the primary user. Simulation results show that the proposed algorithm provides about 3 times improvement in channel utilization compared to the system proposed in [1], with a slight degradation in collision probability. It is also observed that the proposed scheme performance is robust to variations in the primary user behavior.