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A Distributed Relay Selection Algorithm Using Game on Real-Time Testbed

机译:使用游戏在实时测试用游戏的分布式继电器选择算法

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Game theory has made great contributions to Cognitive Radio (CR) algorithm design and it calls up wide interest of CR researchers, while the considerable iterations and the operation complexity would hinder its implementation. And the evaluation under practical environment is an indispensable step before its application. To alleviate the concerns, we propose a distributed relay selection algorithm based on Stackelberg Game and overcome the challenges caused by the high calculation complexity to make our strategy applicable. Moreover, we utilize a real time testbed to evaluate the CR MAC algorithm, which contains the necessary components: programmable RF layer, software-defined MAC layer and adaptive network layer to fulfill the requirements of CR research. It is based on system-on-chip processors with strong configure ability which can develop large scale network. We make experiments on our platform to reveal the game equilibrium's properties and verify our scheme's performance in improving the capacity at the destination and secondary user's spectrum utilization efficiency.
机译:博弈论对认知无线电(CR)算法设计做出了巨大贡献,它调用了CR研究人员的广泛兴趣,而相当大的迭代和操作复杂性会阻碍其实施。在实际环境下的评估是其应用前的不可或缺的一步。为了缓解关注,我们提出了一种基于Stackelberg游戏的分布式继电器选择算法,克服了高计算复杂性引起的挑战,使我们的策略适用。此外,我们利用了实时测试平台来评估CR MAC算法,该CR MAC算法包含必要的组件:可编程RF层,软件定义的MAC层和自适应网络层,以满足CR研究的要求。它是基于片内处理器,具有强大的配置能力,可以开发大规模网络。我们对我们的平台进行实验,揭示游戏均衡的属性,并验证我们的方案在提高目的地和次要用户频谱利用效率的容量方面的性能。

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