Telecom Big Data Assisted BS Resource Analysis for LTE/5G Systems

2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS) Pub Date : 2019-10-01 DOI:10.1109/IUCC/DSCI/SmartCNS.2019.00042

Lexi Xu, Xuefeng Chen, Liang Zhao, Xin Hu, Nan Jiang, Yuting Luan, Xinzhou Cheng, Jie Gao

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引用次数: 14

Abstract

Due to the diverse services and high rate requirements of telecom users, mobile cellular systems envisage the challenges of high resource usage, especially the base station (BS) in the hot-spot area. This paper investigates on telecom big data of LTE/5G systems, and then we design a telecom big data assisted comprehensive BS resource analysis (CBSRA) algorithm. CBSRA algorithm considers six categories of resource data/indicators. Then, CBSRA algorithm judges the usage level of each indicator. Finally, CBSRA algorithm takes the comprehensive analysis and outputs the results. We implement the CBSRA algorithm in a realistic cellular system in China, and the proposed algorithm can assist operator to effectively detect BS with high resource usage.

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电信大数据辅助LTE/5G系统BS资源分析

由于电信用户对业务的多样化和速率的高要求，移动蜂窝系统面临着高资源利用率的挑战，特别是热点区域的基站(BS)。本文对LTE/5G系统的电信大数据进行了研究，在此基础上设计了一种电信大数据辅助综合BS资源分析(CBSRA)算法。CBSRA算法考虑六类资源数据/指标。然后，CBSRA算法判断各指标的使用水平。最后，CBSRA算法进行综合分析并输出结果。我们将CBSRA算法在中国实际蜂窝系统中实现，该算法可以帮助运营商有效地检测到资源利用率高的BS。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)

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