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Dynamic Spectrum Access Scheme of Joint Power Control in Underlay Mode Based on Deep Reinforcement Learning

机译:基于深度强化学习的底层模式联合功率控制动态频谱接入方案

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With the increasing complexity of wireless networks and the increasing shortage of spectrum resources, a novel dynamic spectrum access (DSA) solution is urgently needed. For complex and dynamic cognitive radio networks (CRN), this paper proposes a joint DSA and power control scheme based on deep reinforcement learning (DRL). In order to improve the convergence speed of the algorithm, the DRL is improved to a hierarchical DRL, centralized DSA is implemented through CBS, and distributed power control is implemented at each secondary user (SU). Sufficient simulation experiments show that the proposed algorithm has faster convergence speed and lower packet loss.
机译:随着无线网络的复杂性越来越复杂地和频谱资源的不断缺点,迫切需要一种新型动态频谱访问(DSA)解决方案。对于复杂和动态认知无线电网络(CRN),本文提出了一种基于深增强学习(DRL)的联合DSA和功率控制方案。为了提高算法的收敛速度,DRL改进于分层DRL,集中式DSA通过CBS实现,并且在每个辅助用户(SU)处实现分布式功率控制。足够的仿真实验表明,所提出的算法具有更快的收敛速度和较低的数据包丢失。

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