Coexistence Mechanism of LTE and WiFi Based on Reinforcement Learning in Heterogeneous Networks

被引：0

作者：

Lin Y.-W. ^{[1
,2
]}

机构：

[1] College of Information Science and Technology, Qingdao University of Science and Technology, Qingdao

[2] Postdoctoral Workstation of Haier Group, Qingdao

来源：

Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China | 2021年 / 50卷 / 03期

关键词：

5G; LTE-U; Queuing theory; Reinforcement learning; WiFi;

D O I：

10.12178/1001-0548.2019303

中图分类号：

学科分类号：

摘要：

The coexistence mechanism of LTE-U (long term evolution - unlicensed) and WiFi in 5G heterogeneous wireless networks is discussed. Q learning based - almost blank subframe (QL-ABS) configuration mechanism is proposed for LTE-U. In the mechanism, the queuing theory is used to model the heterogeneous network where LTE-U and WiFi coexist, and the network delay performance is used to represent the input state of Q-learning. The simulation results show that the proposed mechanism can generate a more reasonable almost blank subframe configuration strategy for LTE-U under multiple services and different load conditions through autonomous learning process, and therefore has better online learning performance. Compared with the traditional methods, the proposed mechanism better solves the problem of coexistence between LTE-U and existing WiFi network in the unlicensed frequency bands, and improves the overall delay and online performances of the networks. Copyright ©2020 Journal of University of Electronic Science and Technology of China. All rights reserved.

引用

页码：375 / 381

页数：6

共 19 条

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