一种面向5G蜂窝网络的集中式SDN架构

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摘要翻译：
为了满足高速率、低时延蜂窝宽带应用的需求，计划在2020年前推出第五代(5G)蜂窝无线系统。本文提出了一种新的方法，使第三代合作伙伴计划(3GPP)的5G体系结构与软件定义网络(SDN)的原理相适应。我们提出在5G网络核心中有集中的网络功能来控制网络，端到端。这是通过将5G无线接入网(RAN)中存在的控制功能重新定位到网络核心来实现的，导致被称为gNB的基站转换为纯数据平面节点。这使得RAN和核心网之间的信令成本显著降低。它还提高了系统性能。通过对5G网络的关键性能指标，如网络连接（注册）时间和切换时间的评估，说明了该方案的优点。通过ns-3仿真，我们还展示了由于使用集中式算法进行移动性管理，在连接时间和系统吞吐量方面的改进。
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英文标题：
《A Centralized SDN Architecture for the 5G Cellular Network》
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作者：
Akshatha M. Nayak, Pranav Jha, Abhay Karandikar
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  In order to meet the increasing demands of high data rate and low latency cellular broadband applications, plans are underway to roll out the Fifth Generation (5G) cellular wireless system by the year 2020. This paper proposes a novel method for adapting the Third Generation Partnership Project (3GPP)'s 5G architecture to the principles of Software Defined Networking (SDN). We propose to have centralized network functions in the 5G network core to control the network, end-to-end. This is achieved by relocating the control functionality present in the 5G Radio Access Network (RAN) to the network core, resulting in the conversion of the base station known as the gNB into a pure data plane node. This brings about a significant reduction in signaling costs between the RAN and the core network. It also results in improved system performance. The merits of our proposal have been illustrated by evaluating the Key Performance Indicators (KPIs) of the 5G network, such as network attach (registration) time and handover time. We have also demonstrated improvements in attach time and system throughput due to the use of centralized algorithms for mobility management with the help of ns-3 simulations.
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PDF链接：
https://arxiv.org/pdf/1801.03824

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关键词：Applications Architecture Optimization Improvements registration 平面 control 功能 system gNB