分布式认知无线电网络中基于选择性合作的频谱租赁

Biling Zhang, Kai Chen, Xuerong Gou, Shiduan Cheng
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引用次数: 5

摘要

认知无线电(Cognitive radio, CR)被广泛认为是实现频谱资源高效利用的一种有前途的模式。虽然CR的分层访问模型得到了很多关注,但对于pu主动将其频谱租赁给su并获得一定报酬的频谱租赁模型,研究还不够深入。在本文中,假设一个PU愿意将其带宽租赁一小部分时间以换取选择性合作,我们提出了一个博弈模型来描述PU和su之间的动态交互。在我们的模型中,PU与每个潜在的su进行博弈,并选择最优的su进行合作。我们证明了每个博弈总是存在一个唯一的纳什均衡(NE)。此外,我们还提出了一种简单的分布式算法来实现该模型。仿真结果验证了我们的方法在效用和传输速率方面对PU和SU都有好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectrum leasing via selective cooperation in distributed cognitive radio networks
Cognitive radio (CR) has been widely recognized as a promising paradigm to achieve efficient use of the spectrum resource. While a lot of attention has been paid to the hierarchical access model of CR, the spectrum leasing model in which PUs can actively lease their spectrum to SUs for certain reward has not been studied thoroughly. In this paper, by assuming a PU is willing to lease its bandwidth for a fraction of time to SUs in exchange for selective cooperation, we propose a game model to describe the dynamic interaction between the PU and SUs. In our model, the PU plays a game with each of the potential SUs and selects the best one to cooperate with. We prove that there is always a unique Nash Equilibrium (NE) for each game. Moreover, we propose a simple distributed algorithm for practical implementation of the model. Simulation results verify that our approach can benefit both the PU and the SU in terms of utility and transmission rate.
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