摘要
文章围绕5G通信的崛起和网络切片管理的重要性展开论证,研究并设计面向5G通信的大数据驱动网络切片管理方案。通过设计综合框架,强调算法设计的关键性。同时,针对网络切片算法设计,明确关键性能指标,并深入探讨基于强化学习的动态网络切片调整算法,包括奖励函数和策略的实现。该研究为5G通信中的网络切片管理提供全面且实用的设计和实现方案。
Focusing on the rise of 5G communication and the importance of network slice management,this paper studies and designs a big data-driven network slice management scheme for 5G communication.By designing a comprehensive framework,the key of algorithm design is emphasized.At the same time,aiming at the design of network slicing algorithm,the key performance indexes are defined,and the dynamic network slicing adjustment algorithm based on reinforcement learning is deeply discussed,including the realization of reward function and strategy.This research provides a comprehensive and practical design and implementation scheme for network slice management in 5G communication.
作者
周晓峰
ZHOU Xiaofeng(Hangzhou Simple Point Technology Co.,Ltd.,Hangzhou 310000,China)
出处
《通信电源技术》
2024年第3期40-42,共3页
Telecom Power Technology
关键词
网络切片管理
大数据驱动
强化学习
动态网络调整
network slicing management
big data-driven
reinforcement learning
dynamic network adjustment