通信学报 ›› 2013, Vol. 34 ›› Issue (11): 1-7.doi: 10.3969/j.issn.1000-436x.2013.11.001

• 学术论文 •    下一篇

未知环境中基于图型博弈和multi-Q学习的动态信道选择算法

李方伟,唐永川,朱江   

  1. 重庆邮电大学 移动通信技术重庆市重点实验室,重庆 400065
  • 出版日期:2013-11-25 发布日期:2017-06-23
  • 基金资助:
    国家自然科学基金资助项目;国家自然科学基金资助项目;教育部科学技术研究重点基金资助项目;重庆市科委自然科学基金资助项目;重庆市教委科学技术研究基金资助项目

Dynamic channel selection in unknown environment based on graphical game and multi-Q learning

Fang-wei LI,Yong-chuan TANG,Jiang ZHU   

  1. Chongqing Key Lab of Mobile Communications Technology gqing University of Posts and Telecommunications, Chongqing 400065, China
  • Online:2013-11-25 Published:2017-06-23
  • Supported by:
    The National Natural Science Foundation of China;The National Natural Science Foundation of China;The Key Project of Chinese Ministry of Education;The Natural Science Foundation of Chongqing Science and Technology Commission;The Science and Technology Research Project of Chongqing Education Commission

摘要:

研究了分布式无线网络中,没有任何信息交换、也没有环境变化先验知识情况下的动态信道接入算法。运用图型博弈模型对用户的实际拓扑进行建模分析,证明了此博弈模型存在纯策略纳什均衡并且此纳什均衡是全局最优解。同时,采用multi-Q学习求解模型的纯策略纳什均衡解。仿真实验验证了multi-Q学习能获得较高的系统容量以及在图型博弈模型中用户的效用主要由节点的度决定,而与用户数量无直接关系。

关键词: 动态信道选择, 图型博弈, multi-Q学习, 纯策略纳什均衡

Abstract:

For the problem of dynamic channel selection in unknown distributed environment without a priori knowledge and information exchange, multi-Q learning was proposed. The dynamic channel selection problem was formulated the existence of pure strategy Nash equilibrium in graphical game was proved. At the same time, the pure strategy Nash equi-librium was proved to be global optimal solution. Simulation results show that multi-Q learning achieves high system capacity and utility of users in the graphical game are determined mainly by the degree of the node without direct relationship to the number of users.

Key words: dynamic channel selection, graphical game, multi-Q learning, pure strategy Nash equilibrium

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