Steady-state Markov chain analysis for heterogeneous cognitive radio networks

Cognitive radio technology has been widely researched to improve the spectrum usage efficiency. Modeling of the spectrum occupancy in a cognitive framework including licensed and unlicensed users with various traffic conditions, is a prior requirement to do the system analysis. In this paper, we develop a continuous-time Markov chain model to describe the radio spectrum usage, and derive the transition rate matrix for this model. In addition, we perform steady-state analysis to analytically derive the probability state vector. The proposed model and derived expressions are compared to the existing models, and examined through numerical analysis.