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A MAC level strategy for dynamic resource allocation in Cognitive Radio tactical networks

机译:认知无线电战术网络中用于动态资源分配的MAC级策略

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The ability to continuously self-adapt to the variations of the radio environment will be an interesting issue for future tactical radio networks. Cognitive Radio (CR) is the main enabling paradigm allowing the self-adaptation process in military communications minimizing the human intervention in the network management operations. In this paper we provide a MAC-level solution based on a game theoretic framework that covers these open issues. Thinking to the CR devices in the network as players of the same game, the resource allocation problem can be formulated as a S-Modular Game, since it provides a set of helpful tools aimed at defining multi-objective distributed algorithms in the radio-communications context. On the base of the proposed solution, CR devices are able to hierarchically self-configure the network and share the radio resources in a fair and energy-efficient way. Simulation results presented in this paper has been obtained within the CORASMA project and they show the good performance of the proposed solution for cognitive radio tactical networks.
机译:对于未来的战术无线电网络,不断适应无线电环境变化的能力将是一个有趣的问题。认知无线电(CR)是主要的允许范式,它允许军事通信中的自适应过程将对网络管理操作的人为干预最小化。在本文中,我们提供了一个基于博弈论框架的MAC级解决方案,涵盖了这些未解决的问题。将网络中的CR设备视为同一游戏的玩家,资源分配问题可以表述为S-模块化游戏,因为它提供了一组旨在定义无线电通信中多目标分布式算法的有用工具。上下文。在提出的解决方案的基础上,CR设备能够以公平,节能的方式对网络进行分层自配置并共享无线电资源。本文提出的仿真结果是在CORASMA项目中获得的,它们显示了所提出的认知无线电战术网络解决方案的良好性能。

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