当前位置: X-MOL 学术IEEE Photon. J. › 论文详情
Optimizing Handover Parameters by Q-Learning for Heterogeneous Radio-Optical Networks
IEEE Photonics Journal ( IF 2.729 ) Pub Date : 2019-11-18 , DOI: 10.1109/jphot.2019.2953863
Sihua Shao; Guanxiong Liu; Abdallah Khreishah; Moussa Ayyash; Hany Elgala; Thomas D. C. Little; Michael Rahaim

Existing literature studying the access point (AP)-user association problem of heterogeneous radio-optical networks either investigates quasi-static network selection or only considers vertical handover (VHO) dwell time from optical to radio. The quasi-static assumption can result in outdated decisions for highly mobile scenarios. Solely focusing on the optical to radio handover ignores the importance of dwell time for VHO from radio to optical. In this paper, we propose a flexible and holistic framework, that runs a self-optimizing algorithm at the centralized coordinator (CC). This CC resides in the LTE eNodeB and controls the handover parameters of all the visible light communication (VLC) APs under the coverage of the LTE eNodeB. Based on Q-learning approach, the algorithm optimizes the time-to-trigger ( $TTT$ ) values for VHO between LTE and VLC. Case studies are performed to validate the considerable gain in terms of average throughput by optimizing $TTT$ s. We evaluate the impact of learning parameters on the optimal throughput and convergence speed through trace-driven simulations. The simulation results reveal that the Q-learning based algorithm improves the average throughput of mobile device by 25% when compared to the fixed $TTT$ scheme. Furthermore, this algorithm is capable of self-optimizing handover parameters in an online manner.
更新日期:2020-01-17

 

全部期刊列表>>
Springer Nature 2019高下载量文章和章节
化学/材料学中国作者研究精选
《科学报告》最新环境科学研究
ACS材料视界
自然科研论文编辑服务
中南大学国家杰青杨华明
南开大学陈弓课题组招聘启事
中南大学
材料化学和生物传感方向博士后招聘
课题组网站
X-MOL
北京大学分子工程苏南研究院
华东师范大学分子机器及功能材料
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug