Energy-Efficient On-Demand Cloud Radio Access Networks Virtualization
Energy-Efficient On-Demand Cloud Radio Access Networks Virtualization
复制标题
DOI：
10.1109/glocom.2018.8647929
复制
发表时间：
2018-12
期刊：
影响因子：
--
通讯作者：
Qiang Liu;T. Han;N. Ansari
中科院分区：
文献类型：
--
作者：
Qiang Liu;T. Han;N. Ansari
通过利用云计算的弹性，云无线接入网（C-RAN）便于按需提供无线电和计算资源。本文提出了一种节能的按需C-RAN虚拟化模型，根据业务需求动态提供虚拟C-RAN。通过联合优化远程无线电头（RRH）选择和计算资源分配，使虚拟C-RAN的能耗最小化。由于RRH的选择与计算资源的供给之间存在相互依赖关系，网络能耗最小化问题具有挑战性。我们提出了一种节能的按需C-RAN虚拟化（REACT）算法，分两步解决这个问题。首先，我们使用分层聚类分析（HCA）算法将RRH分组，并为每个RRH组分配一个BBU用于基带信号处理。其次，我们通过优化协同波束形成来确定RRH选择。通过广泛的模拟对所提出算法的性能进行了评估，结果表明，与基线算法相比，所提出的算法减少了高达62%的网络能耗。
By leveraging the elasticity of cloud computing, cloud radio access network (C-RAN) facilitates on-demand radio and computing resource provisioning. In this paper, we propose an energy-efficient on-demand C-RAN virtualization model which dynamically provisions virtual C-RAN according to service demand. The energy consumption of the virtual C-RAN is minimized by jointly optimizing the remote radio head (RRH) selection and computing resource provisioning. The network energy consumption minimization problem is challenging because of the interdependence between the RRH selection and the computing resource provisioning. We propose the energy-efficient on-demand C-RAN virtualization (REACT) algorithm to solve the problem in two steps. First, we cluster RRHs into groups using the hierarchical clustering analysis (HCA) algorithm and assign a BBU to each RRH group for the baseband signal processing. Second, we determine the RRH selection by optimizing the cooperative beamforming. The performance of the proposed algorithm is evaluated through extensive simulations, which shows the proposed algorithm reduces up to 62% of the network energy consumption as compared to a baseline algorithm.