基于改进madpg算法的多智能体竞争频谱切换

Li Shufeng, S. Wei, Pen Yunfei, Zhou Min
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引用次数: 0

摘要

频谱切换是实现动态频谱管理的重要手段。当认知无线网络中存在多个竞争的辅助用户时,环境的动态性将急剧增加,有效的频谱切换将变得困难。本文将频谱切换中多个智能体之间的竞争转化为智能体团队之间的竞争,提出了带辅助网络的多智能体深度确定性策略梯度(madpg)方法来处理环境的动态性。通过预测对手的动作,SU可以提高交接的准确性。仿真实验结果表明,该方法具有较高的体验质量(QoE)。
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Multi-agent Competitive Spectrum Handoff Based on Improved MADDPG Algorithm
Spectrum handoff plays an important role in realizing dynamic spectrum management. When there are multiple competing secondary users (SUs) in a cognitive radio network, the dynamics of the environment will increase dramatically, and efficient spectrum handoffwill become difficult. In this paper, the competition of multiple SUs in spectrum handoff is transformed into competition between SU teams, and the Multi-agent deep deterministic policy gradient (MADDPG) method with auxiliary network is proposed to deal with the dynamics of the environment. By predicting the opponent’s actions, the SU can improve the accuracy of the handoff. In simulation experiments, the proposed method is proved to bring SU with higher Quality of Experience (QoE).
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