A novel proactive soft load balancing framework for ultra dense network

作     者：Miaona Huang Jun Chen Miaona Huang;Jun Chen

作者机构：School of Electrical Engineering and IntelligentizationDongguan University of TechnologyDongguanGuangdong523808China Huawei TechnologyShenzhen518129China 

出 版 物：《Digital Communications and Networks》 (数字通信与网络（英文版）)

年 卷 期：2023年第9卷第3期

页      面：788-796页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 

基　　金：supported in part by the Guangdong Basic and Applied Basic Research Foundation under grant 2020A1515110269. 

主　　题：5G and beyond Proactive load balancing Heterogeneous network Soft load Location prediction 

摘      要：A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network.Due to the user mobility and the coverage of small cells,the network load often becomes unbalanced,resulting in poor network performance.Mobility management has become an important issue to ensure seamless communication when users move between cells,and proactive mobility management is one of the important functions of the active Self-Organizing Network(SON).This paper proposes a proactive mobility management framework for active SON,which transforms the original reactive load balancing into a forward-aware and proactive load balancing.The proposed framework firstly uses the BART model to predict the users’temporal and spatial mobility based on a weekly cycle and then formulate the MLB optimization problem based on the soft load.Two solutions are proposed to solve the above MLB problem.The simulation results show that the proposed method can better optimize the network performance and realize intelligent mobile management for the future network.