基于带缓存的云接入网络最优能效设计

孙远; 李春国; 黄永明; 杨绿溪

doi:10.11999/JEIT180722

基于带缓存的云接入网络最优能效设计

doi: 10.11999/JEIT180722

东南大学信息科学与工程学院南京 210096

基金项目: 国家863计划(2015AA01A703)，国家自然科学基金(61372101, 61671144)

详细信息

作者简介:
孙远：男，1988年生，博士生，研究方向为云接入网络资源分配

李春国：男，1983年生，教授，博士生导师，研究方向为新一代无线通信理论与技术，基于人工智能的视频信息处理，水下无线通信

黄永明：男，1977年生，教授，博士生导师，研究方向为下一代移动通信技术，毫米波MIMO

杨绿溪：男，1964年生，教授，博士生导师，研究方向为下一代移动通信技术，信号与信息处理

通讯作者:
杨绿溪　lxyang@seu.edu.cn

中图分类号: TN92
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- 被引次数: 11
出版历程
- 收稿日期: 2018-07-18
- 修回日期: 2019-01-28
- 网络出版日期: 2019-02-15
- 刊出日期: 2019-07-01

Optimal Energy-efficient Design for Cache-based Cloud Radio Access Network

School of Information Science and Engineering, Southeast University, Nanjing 210096, China

Funds: The National 863 Project of China (2015AA01A703), The National Natural Science Foundation of China (61372101, 61671144)

摘要

摘要: 在云接入网络(Cloud-RAN)中，现有工作大多假定射频拉远头(RRH)不具备缓存功能。然而下一代通信网络具有以内容为中心的特性，因此在Cloud-RAN中考虑带缓存的RRHs也变得有必要。该文考虑在Cloud-RAN中有效设计缓存方案，并通过资源分配有效减轻前程链路负担。假设系统采用正交频分多址接入(OFDMA)技术，通过联合优化子载波(SC)分配，RRH选择与传输功率，最小化系统下行总功耗，并通过拉格朗日对偶分解转化非凸问题，获得最优分配方案。仿真结果表明，比起其它缓存方案，该文提出的优化算法可以有效地提升系统能效，满足未来通信需求。
- 云接入网络 /
- 缓存 /
- 能量效率 /
- 算法设计
Abstract: In Cloud Radio Access Network (Cloud-RAN), most of the existing work assumes Remote Radio Heads (RRHs) could not cache content. To better adapt the content-centric feature of next-generation communication networks, it is necessary to consider caching function for RRHs in Cloud-RAN. Motivated by this, this paper intends to design the suitable caching schemes and reduce the burden of fronthaul link burden through resource allocation. It is assumed the system utilizes Orthogonal Frequency Division Multiple Access (OFDMA) technique. A jointly optimization scheme of SubCarrier (SC) allocation, RRH selection, and transmission power is proposed to minimize the total downlink power consumption. To transform the original non-convex problem, a Lagrange dual decomposition is utilized to design the optimal allocation scheme. The experimental results show that the proposed algorithms can effectively improve the energy efficiency of the system, which meets the requirements of green communication in the future.
- Cloud Radio Access Network (Cloud-RAN) /
- Cache /
- Energy Efficiency (EE) /
- Algorithm design

HTML全文

图 1 带缓存Cloud-RAN下行传输结构图

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图 2 RRH个数变化，本文算法最大复杂度变化趋势

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图 3 用户个数变化，本文算法最大复杂度变化趋势

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图 4 前程容量门限变化，多种方案功耗对比

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图 5 单个RRH最大缓存数目变化，多种方案功耗对比

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