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Femtocell双层网络中基于Q-learning的子信道分配方案

杨秀清 陈禹 李正富

杨秀清, 陈禹, 李正富. Femtocell双层网络中基于Q-learning的子信道分配方案[J]. 电子与信息学报, 2017, 39(3): 598-604. doi: 10.11999/JEIT160453
引用本文: 杨秀清, 陈禹, 李正富. Femtocell双层网络中基于Q-learning的子信道分配方案[J]. 电子与信息学报, 2017, 39(3): 598-604. doi: 10.11999/JEIT160453
YANG Xiuqing, CHEN Yu, LI Zhengfu. Subchannel Allocation Scheme for Two-tire Femtocell Networks Based on Q-learning[J]. Journal of Electronics & Information Technology, 2017, 39(3): 598-604. doi: 10.11999/JEIT160453
Citation: YANG Xiuqing, CHEN Yu, LI Zhengfu. Subchannel Allocation Scheme for Two-tire Femtocell Networks Based on Q-learning[J]. Journal of Electronics & Information Technology, 2017, 39(3): 598-604. doi: 10.11999/JEIT160453

Femtocell双层网络中基于Q-learning的子信道分配方案

doi: 10.11999/JEIT160453
基金项目: 

北京市教育委员会科技计划一般项目(KM201710858003)

Subchannel Allocation Scheme for Two-tire Femtocell Networks Based on Q-learning

Funds: 

The Science and Technology Projects of Beijing Municipal Education Commission(KM201710858003)

  • 摘要: 在Femtocell家庭基站(Femtocell Base Station, FBS)组成的异构网络中,为提升网络的频谱效率,FBS与Macrocell宏基站(Macrocell Base Station, MBS)一般要求是同频部署,然而同频部署会产生同信道干扰。为了实现FBS的大规模部署,降低网络同信道干扰影响变得尤为重要。该文提出一种基于Q-learning的子信道分配方案,既保证大量部署的FBS不会对MBS带来过高的跨层干扰,同时也降低了FBS之间的同层干扰。同时针对FBS稀疏部署和密集部署的场景,分别进行了算法的仿真验证,其仿真结果表明该算法降低了干扰,验证了理论的正确性。
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出版历程
  • 收稿日期:  2016-05-03
  • 修回日期:  2016-11-15
  • 刊出日期:  2017-03-19

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