A continuous-time Markov chain model and analysis for cognitive radio networks. (1st January 2012) - Zahmati, Amir Sepasi; Fernando, Xavier; Grami, Ali
Cognitive radio concept has been widely researched to improve the spectrum usage efficiency. Appropriate modelling of the spectrum occupancy by both licensed and unlicensed users is necessary to do clear system analysis in a cognitive framework. In this paper, a continuous-time Markov chain model is developed to better describe the radio spectrum usage. The state space vector and the transition rate matrix that completely describe the system are obtained; a steady-state analysis is performed and the stationary state probability (SSP) vector is derived. In addition, we take into account the inaccuracy of the existing spectrum sensing model (missed opportunities), and derive an improved expression for the maximum throughput of secondary users as a function of the primary user traffic parameters and the achieved opportunity ratio (AOR). The optimum sensing period that maximises AOR is also analytically obtained. The proposed model and the derived expressions were examined through numerical analysis and compared with the existing models. This model is very general and applicable to systems with N secondary users in the vicinity of the primary user.