基于强化学习的认知无线网络病毒对抗策略

VIRUS COUNTERMEASURES IN COGNITIVE WIRELESS NETWORKS BASED ON REINFORCEMENT LEARNING

  • 摘要: 认知无线网络通过允许次用户访问主用户拥有的授权频带,显著提高了无线电频谱的利用率。认知无线网络存在被病毒入侵主用户占用授权频带进而降低次用户通信量的可能。提出一种基于多智能体强化学习的认知无线网络病毒对抗策略,通过优化次用户动态路由策略,把病毒攻击对次用户造成的影响降到最低。

     

    Abstract: Cognitive wireless networks improve the utilization of the radio spectrum by allowing secondary users (SU) to access licensed bands owned by primary users. Cognitive wireless network has the possibility that viruses invade primary users and occupy the licensed frequency band to reduce the traffic of secondary users. This paper proposes a cognitive wireless network virus countermeasure strategy based on multi-agent reinforcement learning, which minimizes the impact of virus attack on SUs by optimizing the dynamic routing strategy of SUs.

     

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