Hyper-Erlang distribution model and its application in wireless mobille networks
Wireless Networks - Special issue: Design and modeling in mobile and wireless systsems
Performance Analysis and Modeling of Digital Transmission Systems (Information Technology: Transmission, Processing and Storage)
Markov chain existence and Hidden Markov models in spectrum sensing
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
Opportunistic spectrum access for energy-constrained cognitive radios
IEEE Transactions on Wireless Communications
Optimal Transmission Strategies for Dynamic Spectrum Access in Cognitive Radio Networks
IEEE Transactions on Mobile Computing
Cross-layered design of spectrum sensing and MAC for opportunistic spectrum access
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Sensing-Throughput Tradeoff for Cognitive Radio Networks
IEEE Transactions on Wireless Communications
IEEE Transactions on Information Theory
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework
IEEE Journal on Selected Areas in Communications
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In this paper, we propose a novel transmission probability scheduling (TPS) scheme for the opportunistic spectrum access based cognitive radio system (OSA-based CRS), in which the secondary user (SU) optimally schedules its transmission probabilities in the idle period of the primary user (PU), to maximize the throughput of the SU over a single channel when the collision probability perceived by the PU is constrained under a required threshold. Particularly, we first study the maximum achievable throughput of the SU when the proposed TPS scheme is employed under the assumption that the distribution of the PU idle period is known and the spectrum sensing is perfect. When the spectrum sensing at the SU is imperfect, we thoroughly quantify the impact of sensing errors on the SU performance with the proposed TPS scheme. Furthermore, in the situation that the traffic pattern of the PU and its parameters are unknown and the spectrum sensing is imperfect, we propose a predictor based on hidden Markov model (HMM) for the proposed TPS scheme to predict the future PU state. Extensive simulations are conducted and show that the proposed TPS scheme with the HMM-based predictor can achieve a reasonably high SU throughput under the PU collision probability constraint even when the sensing errors are severe.