Adaptive channel access in spectrum database-driven cognitive radio networks

Providing adequate and reliable spectrum resources for unlicensed users in spectrum database-based cognitive radio networks is very challenging, mainly due to the dynamic resource availability induced by the licensed users' activities and radio environment. In this paper, we propose an adaptive spectrum access method based on spectrum database for cognitive radio (CR) networks. While making decision to access the licensed spectrum, the secondary users (SUs) not only use the spectrum information informed by the spectrum database but also use the local sensing to confirm the specific condition of the spectrum. The adaptive sensing and access process is modeled as an optimal decision process by maximizing the achievable throughput of CR networks. The dynamic programming algorithm is developed to find the optimal sensing and access policy for each SU. Simulation results show that the proposed sensing and access policies can provide reliability guarantees for finding spectrum opportunities in terms of dynamic radio environment.