Q-learning based handoff algorithm for satellite system with ancillary terrestrial component

Dan-ni XIONG; Yi LI

doi:10.11959/j.issn.1000-436x.2015240

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Q-learning based handoff algorithm for satellite system with ancillary terrestrial component

Academic communication | 更新时间：2024-06-05

- Q-learning based handoff algorithm for satellite system with ancillary terrestrial component
- Journal on Communications Vol. 36, Issue 9, Pages: 252-258(2015)
- 作者机构：
  
  北京邮电大学泛网无线通信教育部重点实验室，北京100876
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-436x.2015240
  CLC： TN927
- Online First：2015-09，
  
  Published：25 September 2015
- 稿件说明：
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Dan-ni XIONG, Yi LI. Q-learning based handoff algorithm for satellite system with ancillary terrestrial component[J]. Journal on Communications, 2015, 36(9): 252-258.
DOI：

Dan-ni XIONG, Yi LI. Q-learning based handoff algorithm for satellite system with ancillary terrestrial component[J]. Journal on Communications, 2015, 36(9): 252-258. DOI： 10.11959/j.issn.1000-436x.2015240.

摘要

基于地面辅助基站（ATC）的星地融合网络（MSS-ATC）具有覆盖范围广、用户体验佳的特点，切换机制是该融合网络主要研究的问题之一。针对卫星链路时延大、卫星网用户速度范围广的特点，综合考虑了用户接收信号强度（RSS）和用户运动速度，提出了一种基于卡尔曼滤波和Q学习的切换决策算法。比较了所提算法与传统算法在链路衰减率、切换次数和网络收益的性能，实验结果表明所提算法在性能上得到了很大的提升，并且能很好地适应高速运动状态。

Abstract

In the integrated satellite-terrestrial communication system

i.e.

mobile satellite system with ancillary terres-trial component (MSS-ATC)

the long transmission delay of satellite link was a huge challenge which may lead to high handoff dropping probability.In order to address this problem

a novel handoff decision strategy was proposed based on the predictive RSS and Q-learning algorithm.Extensive simulation results demonstrate that the proposed scheme can de-crease the handoff dropping probability

reduce the unnecessary handoff times and maximize the network reward.In ad-dition

the proposed scheme can also adapt to the situation of high-speed movement very well.

关键词

Keywords

references

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