Modeling and analysis of system dynamics and state estimation in cognitive radio networks

Cognitive radio networks (CRN) are subject of a multidisciplinary research in wireless networking, digital communications, artificial intelligence, and other fields. Special emphasis is given to investigation of the CRN capability of improved RF spectrum utilization by means of dynamic spectrum access (DSA). This paper proposes a new analytic framework for modeling the adaptive behavior of CRN. In particular, a model of the CRN is developed which incorporates sensing of the electromagnetic environment, estimating states of the communication channels, making decisions based on some policy and dynamically switching the transmissions to the channels that are not currently occupied by primary users. The proposed framework is analyzed using mathematical tools of queueing theory and the performance of the CRN is evaluated. We show the impact of sensing rate and the system dynamics on the waiting times of secondary users.