基于强化学习的LTE与WiFi异构网络共存机制

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

该文论述了5G异构无线网络中LTE-U与WiFi的共存机制,提出基于Q学习的LTE-U空白子帧配置机制(QL-ABS)。该机制使用排队论对LTE-U与WiFi共存的异构网络进行建模,使用网络时延性能表征Q学习的输入状态。仿真结果表明,通过自主学习过程,该机制可在多业务不同负载条件下为LTE-U产生较为合理的空白子帧配置策略,具有较好的在线学习性能。较传统方法,该机制更好地解决了LTE-U与现有WiFi网络在非授权频带的共存问题,提升了系统的时延和在线性能。

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.