Leveraging Intelligence from Network CDR Data for Interference Aware Energy Consumption Minimization
Leveraging Intelligence from Network CDR Data for Interference Aware Energy Consumption Minimization
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DOI：
10.1109/tmc.2017.2773609
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发表时间：
2018-07
影响因子：
7.9
通讯作者：
A. Zoha;Arsalan Saeed;H. Farooq;A. Rizwan;A. Imran;M. Imran
中科院分区：
文献类型：
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作者：
A. Zoha;Arsalan Saeed;H. Farooq;A. Rizwan;A. Imran;M. Imran
电池致密化被认为是解决即将到来的产能危机的灵丹妙药。然而，高总能耗和致密化导致的小区间干扰（ICI）增加仍然是两个长期存在的问题。我们提出了一种新颖的网络编排解决方案，可同时最大限度地减少超密集 5G 网络中的能耗和 ICI。所提出的解决方案建立在对来自真实网络的超过 1000 万条 CDR 的大数据分析的基础上，该分析表明真实网络流量模式存在强大的时空可预测性。利用这一点，我们开发了一种新颖的方案来主动调度无线电资源和小蜂窝睡眠周期，从而节省大量能源并减少 ICI，而不会影响用户的 QoS。该方案是通过制定联合能耗和 ICI 最小化问题并通过线性二进制整数规划和基于渐进分析的启发式算法的组合来求解该问题而得出的。评估使用：1) 为米兰市设计的 HetNet 部署，其中大数据分析用于来自意大利电信网络的真实 CDR 数据，以对流量模式进行建模，2) 基于 NS-3 的蒙特卡罗模拟与合成泊松流量表明，与完全频率复用和始终在线的方法相比，在最佳情况下，所提出的方案可以将 HetNet 的能耗降低到 1/8，同时提供相同或更好的 QoS。
Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this, we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, the proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better QoS.