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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的最佳准入控制方案

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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:认知无线电网络有望通过允许无执照的次要用户(SU)机会性地利用主用户(PU)未使用的经许可的频谱来解决频谱短缺问题。在本文中,我们提出了一种最优的准入控制方案,该方案在保证PU的QoS的同时最大化利润。利润最大化问题可表述为半马尔可夫决策过程(SMDP)并推导其相关组成部分。提出了一种线性规划(LP)算法,以获得最优的接纳控制策略。通过向SMDP公式添加约束,还可以考虑为PU提供QoS服务。仿真结果表明,与基于完全共享和阈值的准入控制方案相比,所提出的最优准入控制方案具有更高的收益,并且可以严格限制PU的阻塞概率。

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