AI-Based Optimization of Handover Strategy in Non-Terrestrial Networks

查看全文 作　　者：ZHANG [1]Chenchen;ZHANG [1]Nan;CAO [1]Wei;TIAN [1]Kaibo;YANG [1]Zhen

机构地区：[1]State Key Laboratory of Mobile Network and Mobile Multimedia Technology,ZTE Corporation,Shenzhen 518055,China

出　　处：《ZTE Communications》索引2021年第19卷第4期,共7页

摘　　要：Complicated radio resource management,e.g.,handover condition,will trouble the user in non-terrestrial networks due to the impact of high mobility and hierarchical layouts which co-exist with terrestrial networks or various platforms at different altitudes.It is necessary to optimize the handover strategy to reduce the signaling overhead and im⁃prove the service continuity.In this paper,a new handover strategy is proposed based on the convolutional neural network.Firstly,the handover process is modeled as a directed graph.Suppose a user knows its future signal strength,then he/she can search for the best handover strategy based on the graph.Secondly,a convolutional neural network is used to extract the underlying regularity of the best handover strategies of different users,based on which any user can make near-optimal handover decisions according to its historical signal strength.Numerical simulation shows that the proposed handover strategy can effi⁃ciently reduce the handover number while ensuring the signal strength. 关键词：convolutional neural network directed graph HANDOVER low earth orbit nonterrestrial network

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AI-Based Optimization of Handover Strategy in Non-Terrestrial Networks

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