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An SMDP-based optimal admission control scheme in cognitive radio networks

机译:认知无线电网络中基于SMDP的最优准入控制方案

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Cognitive radio network is expected to solve the spectrum scarcity by enabling unlicensed secondary users (SUs) to opportunistically utilize the licensed spectrum unused by primary users (PUs). In this paper, we propose an optimal admission control scheme which maximizes the profit while guaranteeing QoS of the PUs. The profit maximization problem is formulated as a Semi-Markov Decision Process (SMDP) and its relevant components are derived. A Linear Programming (LP) algorithm is presented to obtain the optimal admission control policy. QoS provisioning for PUs is also considered by adding constraint to the SMDP formulation. Simulation results show that, the proposed optimal admission control scheme achieves more profit than the Complete Sharing and Threshold-based admission control scheme, and the blocking probability of PUs can be strictly constrained.
机译:期望认知无线电网络通过使未经许可的二级用户(SUS)能够机会利用主要用户(PUS)未使用的许可频谱来解决频谱稀缺性。在本文中,我们提出了一种最佳的准入控制方案,可以在保证脓液QoS时最大化利润。利润最大化问题被制定为半马尔可夫决策过程(SMDP),并导出其相关组件。提出了线性编程(LP)算法以获得最佳录取控制策略。通过向SMDP制剂增加约束,还考虑了对PU的QoS供应。仿真结果表明,所提出的最优录取控制方案比完整共享和基于阈值的准入控制方案实现更多利润,并且脓液的阻塞可能是严格限制的。

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