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计算机工程

• 移动互联与通信技术 • 上一篇    下一篇

一种基于Q学习的网络接入控制算法

冯陈伟,张璘   

  1. (厦门理工学院光电与通信工程学院,福建 厦门 361024)
  • 收稿日期:2015-03-25 出版日期:2015-10-15 发布日期:2015-10-15
  • 作者简介:冯陈伟(1981-),男,讲师、硕士,主研方向:下一代无线通信技术;张璘,讲师、硕士。
  • 基金资助:
    国家自然科学基金青年基金资助项目(61202013);福建省自然科学基金资助项目“多载波通信强非线性射频功放数字预失真算法与实现研究”(2015J01670);福建省中青年教师教育科研A类基金资助项目“基于蜂窝D2D异构网络的无线资源管理技术研究”(JA14233)。

A Network Access Control Algorithm Based on Q-learning

FENG Chenwei,ZHANG Lin   

  1. (School of Opto-electronic and Communication Engineering,Xiamen University of Technology,Xiamen 361024,China)
  • Received:2015-03-25 Online:2015-10-15 Published:2015-10-15

摘要: 下一代无线网络是多种无线接入技术共存的异构网络,要充分利用各种无线网络的资源,需要实现异构网络的融合,但网络融合却面临异构网络环境下的接入请求控制问题。为此,在长期演进、无线局域网、设备直连构成的无线异构网络下,提出一种异构网络接入控制算法。根据不同的业务类型、终端移动性及网络负载状态,利用匹配系数所构成的回报函数,反映网络对相应业务及移动性的贡献程度,通过Q学习算法选择合适的网络接入方式。仿真结果表明,该算法具有高效的在线学习能力,能够有效提升网络在频谱效用和阻塞率方面的性能,实现自主的无线资源管理。

关键词: 异构无线网络, 接入控制, 长期演进, 设备直连, Q学习, 资源管理, 阻塞率, 频谱效用

Abstract: The next generation wireless network is the heterogeneous network of coexistence of a variety of wireless access technology.In order to make full use of the resources of all kinds of wireless network,the integration of heterogeneous network is necessary.However,when it comes to the heterogeneous network integration,the call request access control problem comes.In wireless heterogeneous network composing of Long Term Evolution(LTE),Wireless Local Area Network(WLAN) and Device-to-Device(D2D),an algorithm is presented for heterogeneous wireless network selection.The proposed algorithm based on Q-learning can select the appropriate network for access according to different traffic types,terminal mobility and network load status by using the return function composing of matching coefficient reflecting the network contribution,the corresponding traffic and mobility.Simulation results show that the proposed algorithm has an efficient learning ability to achieve autonomous radio resource management,which effectively improves the spectrum utility and reduces the blocking probability.

Key words: heterogeneous wireless network, access control, Long Term Evolution(LTE), Device-to-Device(D2D), Q-learning, resource management, block probability, spectrum utility

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