摘要
5G网络切片支持增强型移动宽带、超可靠低时延通信和大规模机器类通信三大类业务场景,可以共享物理资源,并保证切片之间隔离性需求。网络切片按需定制、实时部署、动态保障等特性给网络带来了极大的灵活性,但使得网络管理和运维更加复杂和具有挑战性。人工智能(AI)技术是解决网络切片管理复杂性的潜在方案。因此将研究AI和切片管理融合,提出了一个基于AI的智能切片管理架构,详述了智能切片管理流程,并给出部分典型应用案例。
5 G network slicing supports three major service scenarios including enhanced mobile broadband( eMBB), ultra-reliable low-latency communication( uRLLC), and massive machine-type communication( mMTC). It can share physical resources and ensure the isolation requirements between slices. Network slicing features, such as on-demand customization, real-time deployment, and dynamic guarantee, enable network flexibility, but make network management and operation more complex and challenging. Artificial intelligence( AI) technology is a potential solution to the complexity of network slice management. Therefore, this article will study the integration of AI and network slice management, propose an AI-based intelligent slice management architecture, introduce the intelligent slice management processes in detail, and present some typical application cases.
作者
徐丹
王海宁
袁祥枫
朱雪田
Xu Dan;Wang Haining;Yuan Xiangfeng;Zhu Xuetian(China Telecom Research Institute AI R&D Center,Beijing 102209,China;China Telecom Intelligent Network and Terminal Research Institute,Beijing 102209,China)
出处
《电子技术应用》
2020年第1期6-11,16,共7页
Application of Electronic Technique
关键词
网络切片
人工智能
智能切片管理
network slicing
artificial intelligence
intelligent slice management
作者简介
徐丹(1993-),女,硕士,工程师,主要研究方向:网络人工智能、网络切片;王海宁(1982-),女,硕士,教授级高级工程师,主要研究方向:网络人工智能应用、NFV、ETSI ENI网络智能化标准;袁祥枫(1993-),男,硕士,工程师,主要研究方向:电信网络相关人工智能算法与应用。
