A learning algorithm for TWDM-PON' DWBA with 5G fronthaul networks

被引：4
|
作者：
Liang, Siyuan [1 ,2 ]
Zhao, Feng [1 ]
Jiang, Wenli [1 ]
机构：
[1] Xian Univ Posts & Telecommun, Shaanxi Key Lab Informat Commun Network & Secur, Xian 710121, Shaanxi, Peoples R China
[2] Xi An Jiao Tong Univ, 28 Xianning West Rd, Xian 710049, Shaanxi, Peoples R China
来源：
OPTICAL FIBER TECHNOLOGY | 2019年 / 53卷
基金：
中国国家自然科学基金;
关键词：
5G networks; Dynamic wavelength and bandwidth allocation; NG-PON2; Q-learning algorithm; TWDM-PON;
D O I：
10.1016/j.yofte.2019.102039
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Time and wavelength-division multiplexed passive optical network (TWDM-PON) is expected to be the fronthaul networks of 5G, which requires low latency and large bandwidth. In this paper, we propose a Q-learning based dynamic wavelength and bandwidth allocation (DWBA) algorithm for TWDM-PON. Simulation results show that the proposed DWBA algorithm can reduce the number of active channels by 40% and provide larger bandwidth with same wavelength number in comparation with the existing algorithms while satisfying the latency requirement of 5G fronthaul networks.
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收藏
页数：5
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