Elements of information theory
Elements of information theory
Modeling and analysis of stochastic systems
Modeling and analysis of stochastic systems
Queueing Networks and Markov Chains
Queueing Networks and Markov Chains
NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks
IEEE Transactions on Mobile Computing
Markov chain existence and Hidden Markov models in spectrum sensing
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
Primary-prioritized Markov approach for dynamic spectrum allocation
IEEE Transactions on Wireless Communications
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency
IEEE Communications Magazine
Dynamic spectrum access in open spectrum wireless networks
IEEE Journal on Selected Areas in Communications
A Hybrid Spectrum Sensing Method for Cognitive Sensor Networks
Wireless Personal Communications: An International Journal
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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.