A prediction approach for MAC layer sensing in cognitive radio networks

In cognitive radio (CR) networks, spectrum sensing has been recognized as the crucial issue of achieving the secondary usage of spectrum. The physical (PHY) layer sensing focuses on how to detect the presence of primary user (PU) signals rapidly and robustly, while the medium access control (MAC) layer sensing concentrates on designing the coordination and communication protocols for secondary users (SUs). In this paper, we address the issues for MAC layer sensing and propose an exponential weighted moving average (EWMA) based approach to predict the spectrum occupancy information. Numerical results show our prediction scheme performs well in the considered scenario. Based on the predicted spectrum occupancy information, the prospect of better scheduling of the MAC layer sensing can be achieved.