Prophet model and Gaussian process regression based user traffic prediction in wireless networks
Prophet model and Gaussian process regression based user traffic prediction in wireless networks作者机构：National Mobile Communications Research Laboratory Southeast University
出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))
年 卷 期：2020年第63卷第4期
页 面：207-214页
核心收录：
学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统]
基 金：partially supported by National Key Research and Development Project (Grant No. 2018YFB1802402) Huawei Tech. Co., Ltd
主 题：wireless networks traffic prediction prophet model Gaussian process regression
摘 要：User traffic prediction is an important topic for wireless network operators. A user traffic prediction method based on Prophet and Gaussian process regression is proposed in this paper. The proposed method first employs discrete wavelet transform to decompose the user traffic time series to high-frequency component and low-frequency component. The low-frequency component bears the long-range dependence of user network traffic, while the high-frequency component reveals the gusty and irregular fluctuations of user network traffic. Then Prophet model and Gaussian process regression are applied to predict the two components respectively based on the characteristics of the two components. Experimental results demonstrate that the proposed model outperforms the existing time series prediction method.
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