北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2023, Vol. 46 ›› Issue (3): 25-30.

• 人工智能使能网络通信 • 上一篇    下一篇

一种采用dueling-DDQN算法的无线网络MAC协议

杨华1,耿烜1,孔宁2   

  1. 1. 上海海事大学 信息工程学院 2. 众格智能科技有限公司
  • 收稿日期:2022-01-28 修回日期:2022-10-04 出版日期:2023-06-28 发布日期:2023-06-05
  • 通讯作者: 杨华 E-mail:yanghua@shmtu.edu.cn
  • 基金资助:
    上海市教委科研创新项目(2101070010E00121)

A MAC Protocol for Wireless Networks Using Dueling-DDQN Algorithm

YANG Hua1, GENG Xuan1, KONG Ning2   

  • Received:2022-01-28 Revised:2022-10-04 Online:2023-06-28 Published:2023-06-05

摘要:

为了在快速变化的无线通信网络中实现系统吞吐量最大化,提出了一种采用竞争架构深度双 Q 网络(dueling-DDQN)算法的媒体访问控制协议。该协议将竞争架构 Q 网络算法中的 值运算方法应用于深度双Q网络中的 值计算,结合了竞争架构 Q 网络和深度双 Q 网络的优点,既能够提高 值的计算准确率和收敛性能,又解决了过度估计的问题,提升了系统的整体性能和鲁棒性。仿真实验结果表明,在无线通信系统中,相较于传统深度 Q 网络媒体访问控制(MAC)协议,当所提协议与时分多址协议和 ALOHA 协议共存时,有效地减少了收敛时间且提高了系统的总吞吐量。

关键词: 深度强化学习, 竞争架构 Q 网络, 深度双 Q 网络, 媒体访问控制协议, 吞吐量

Abstract:

A medium access control protocol using dueling-deep double Q-network (dueling-DDQN) algorithm is proposed to maximize the system throughput in the rapidly changing wireless communication networks. The proposed protocol applies the q value calculation method of the dueling deep Q-network to calculate the q value of the deep double Q-network,which combines the advantages of dueling deep Q-network and deep double Q-network. Thus, it cannot only increase the calculation accuracy of the q value and the convergence performance, but also solve the problem of overestimation, that improves the overall performance and robustness of the system. The simulation results demonstrate that the proposed protocol coexisting with time division multiple access protocol and ALOHA protocol in wireless communication systems, is effective to reduce the convergence time and increase the total system throughput when comparing to the traditional deep Q-network medium access control(MAC) protocol.

Key words: deep reinforcement learning, dueling deep Q-network, deep double Q-network, medium access control protocols, throughput

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