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

Renato Pucci, L. Ronga, E. D. Re
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引用次数: 2

Abstract

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.
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认知无线电战术网络中动态资源分配的MAC级策略
持续自适应无线电环境变化的能力将是未来战术无线电网络的一个有趣问题。认知无线电(CR)是军事通信中允许自适应过程的主要使能范式,最大限度地减少了网络管理操作中的人为干预。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,涵盖了这些开放问题。考虑到网络中的CR设备是同一游戏的参与者,资源分配问题可以被表述为s -模块化游戏,因为它提供了一套有用的工具,旨在定义无线电通信环境中的多目标分布式算法。在此基础上,CR设备能够分层自配置网络,以公平和节能的方式共享无线电资源。本文给出的仿真结果已在CORASMA项目中获得,表明了所提出的解决方案在认知无线电战术网络中的良好性能。
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