对5G NR深度睡眠状态适应的KPI影响

Richard Tano, Martina Tran, P. Frenger
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引用次数: 4

摘要

在本文中,我们评估了引入可能部署在5G NR基站中的新深度睡眠状态特征对性能的影响。我们通过应用一个更新的电力消耗模型来评估对交通性能和能源效率的影响。先前提出的权力模型可能过于乐观,因此研究了一个新的更保守的权力模型的影响。还进行了灵敏度分析,以了解功率模型的各种参数设置对kpi的影响。在评估中,我们表明,通过使用更保守的功率模型可以实现的节能仍然非常高,并且如果以周到的方式应用睡眠状态,对用户性能的影响可以很小。在5G网络场景中,可以节省高达80%的能源。性能影响可以限制在文件传输的几个百分点的额外延迟。还发现,即使对功率模型进行相当大的修改,也会得到类似的结果。
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KPI Impact on 5G NR Deep Sleep State Adaption
In this paper we evaluate the performance impact of introducing the new deep sleep state features that may be deployed in 5G NR base stations. We evaluate the effects on traffic performance and energy efficiency by applying an updated power consumption model. Previously proposed power models may be too optimistic and thus the impact of a new more conservative power model has been investigated. A sensitivity analysis is also performed to understand the effects on the KPIs with various parameter settings of the power model. In the evaluations we show that the energy savings that is achievable by using a more conservative power model is still very high and that the impact on user performance can be small if the sleep states are applied in a thoughtful manner. Up to 80% energy savings is possible to achieve in a 5G hetnet scenario. The performance impact can be limited to a few percent extra delay on file transmissions. It is also found that even quite large modifications to the power model give similar results.
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