大数据辅助支持CRAN的5G SON架构

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of ICT Research and Applications Pub Date : 2019-09-30 DOI:10.5614/itbj.ict.res.appl.2019.13.2.1

K. Khurshid, A. Khan, Haroon Siddiqui, Imran Rashid, M. Hadi

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引用次数: 13

摘要

大数据、物联网（IoT）和5G网络技术的最新发展为IT行业和移动网络运营商提供了大量机会。5G蜂窝技术有望为大量物联网设备提供连接，同时满足低延迟数据传输要求。当前4G网络的一个缺陷是，来自物联网设备和移动节点的数据仅传递到云，通信基础设施在数据分析中没有发挥作用。该系统不仅可以将数据传递到云端，还可以为数据分析和决策做出贡献。在这项工作中，利用新兴技术CRAN、NVF和SDN的知识，提出了一种大数据驱动的自优化5G网络设计。此外，还讨论了5G网络优化中的一些技术障碍。通过一个案例来证明大数据在解决资源分配问题方面的辅助作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Big Data Assisted CRAN Enabled 5G SON Architecture

The recent development of Big Data, Internet of Things (IoT) and 5G network technology offers a plethora of opportunities to the IT industry and mobile network operators. 5G cellular technology promises to offer connectivity to massive numbers of IoT devices while meeting low-latency data transmission requirements. A deficiency of the current 4G networks is that the data from IoT devices and mobile nodes are merely passed on to the cloud and the communication infrastructure does not play a part in data analysis. Instead of only passing data on to the cloud, the system could also contribute to data analysis and decision-making. In this work, a Big Data driven self-optimized 5G network design is proposed using the knowledge of emerging technologies CRAN, NVF and SDN. Also, some technical impediments in 5G network optimization are discussed. A case study is presented to demonstrate the assistance of Big Data in solving the resource allocation problem.

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来源期刊

Journal of ICT Research and Applications COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

1.60

自引率

0.00%

发文量

审稿时长

24 weeks

期刊介绍： Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management. Authors are invited to submit articles that have not been published previously and are not under consideration elsewhere.