Anticipatory QoE Mechanisms for 5G Data Analytics

R. Vidhya, P. Karthik, S. Jamadagni
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引用次数: 4

Abstract

3GPP which is working on the 5G specification is also working on the NWDAF (Network Data Analytics Function) which is used for data collection and data analytics in a centralized manner in the 5G Core. The 5G Network elements and/or the OAM (Operations and Network Management) can decide how to use the data analytics provided by NWDAF to improve the overall system performance. The way NWDAF is used is left to the imagination of the operators, but some of the use cases belong to one or several domains, e.g. QoS, traffic steering, network dimensioning. In this paper, we show how to use the NWDAF to address QoE issues. QoS is evaluated by monitoring KPIs, but this alone is insufficient for addressing QoE *issues as KPIs does not necessarily address QoE. We show that the anticipatory AI functionality will help address QoE in a mobile video streaming use case.
5G数据分析的预期QoE机制
正在制定5G规范的3GPP也在研究NWDAF(网络数据分析功能),该功能用于5G核心中的集中数据收集和数据分析。5G网元和/或OAM(运营和网络管理)可以决定如何使用NWDAF提供的数据分析来提高整体系统性能。NWDAF的使用方式留给了运营商的想象,但是一些用例属于一个或几个领域,例如QoS,流量导向,网络维度。在本文中,我们展示了如何使用NWDAF来解决QoE问题。QoS是通过监控kpi来评估的,但仅凭这一点不足以解决QoE *问题,因为kpi不一定能解决QoE。我们展示了预期的AI功能将有助于解决移动视频流用例中的QoE。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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