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Energy-efficient cloud radio access networks by cloud based workload consolidation for 5G

机译:通过基于云的5G工作负载整合实现高能效的云无线电接入网络

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Next-generation cellular systems like fifth generation (5G) are expected to experience tremendous traffic growth. To accommodate such traffic demand, there is a need to increase the network capacity that eventually requires the deployment of more base stations (BSs). Nevertheless, BSs are very expensive and consume a lot of energy. With growing complexity of signal processing, baseband units are now consuming a significant amount of energy. As a result, cloud radio access networks (C-RAN) have been proposed as an energy efficient (EE) architecture that leverages cloud computing technology where baseband processing is performed in the cloud. This paper proposes an energy reduction technique based on baseband workload consolidation using virtualized general purpose processors (GPPs) in the cloud. The rationale for the cloud based workload consolidation model is to switch off idle baseband units (BBUs) to reduce the overall network energy consumption. The power consumption model for C-RAN is also formulated with considering radio side, fronthaul and BS cloud power consumption. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution (LTE) RAN system. The proposed scheme saves up to 80% of energy during low traffic periods and 12% during peak traffic periods compared to baseline LTE system. Moreover, the proposed scheme saves 38% of energy compared to the baseline system on a daily average.
机译:像第五代(5G)这样的下一代蜂窝系统有望实现巨大的流量增长。为了适应这种流量需求,需要增加网络容量,这最终需要部署更多的基站(BS)。然而,BS非常昂贵并且消耗大量能量。随着信号处理复杂性的增加,基带单元现在正在消耗大量能量。结果,已经提出了云无线电接入网(C-RAN)作为利用云计算技术的节能(EE)架构,其中在云中执行基带处理。本文提出了一种在云中使用虚拟化通用处理器(GPPs)的,基于基带工作负载整合的节能技术。基于云的工作负载合并模型的基本原理是关闭空闲的基带单元(BBU),以减少总体网络能耗。还考虑了无线电侧,前传和BS云的功耗来制定C-RAN的功耗模型。仿真结果表明,与现有的分布式长期演进(LTE)RAN系统相比,该方案实现了更高的能源性能。与基准LTE系统相比,拟议的方案在低流量时段可节省多达80%的能量,在高峰流量时段可节省12%的能量。此外,与基线系统相比,该方案每天平均节省38%的能源。

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