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Capacity Maximization in Cognitive Networks: A Stackelberg Game-Theoretic Perspective

机译:认知网络中的容量最大化:Stackelberg博弈论的观点

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Contrary to previous works, we focus on cooperation and competition relationship and the interactive dynamic behavior between multiple primary users (PUs) and secondary users (SUs) in a multiple cognitive interference channel context. Because of different levels of context information perceived by different types of players, e.g. the PUs and the SUs, and unbalanced nature of the spectrum priority among the multi-SUs/Pus in this setting, we investigate capacity maximization using the Stackelberg game modeling approach. Especially, we analyze the multi-leaders and multi-followers case, and further give a one-by-one case for making this model clear. Some conclusions are given via theorems. In addition, we propose the distributed iterative water-filling algorithms (IWFA) for pursuing Nash equilibrium solution (NES) and the Stackelberg equilibrium solution (SES) with low implementation complexity after analyzing and deriving the newly formulated game model in detail. Simulations results verify the performance of the proposed approaches in this paper.
机译:与以前的工作相反,我们关注合作和竞争关系以及在多个认知干扰通道上下文中多个主要用户(PU)和次要用户(SU)之间的互动动态行为。由于不同类型的玩家所感知的上下文信息级别不同,例如PU和SU,以及在这种情况下多SU / Pus之间频谱优先级的不平衡性质,我们使用Stackelberg博弈建模方法研究容量最大化。尤其是,我们分析了多领导者和多跟随者的情况,并进一步给出了一个清晰的模型来进行逐一说明。通过定理给出了一些结论。此外,在详细分析和推导新制定的博弈模型之后,我们提出了一种用于实现纳什均衡解决方案(NES)和斯塔克尔伯格均衡解决方案(SES)且实现复杂度较低的分布式迭代注水算法(IWFA)。仿真结果验证了本文提出方法的性能。

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