{"title":"5G的成本效益移动管理","authors":"Anna Prado, Fidan Mehmeti, W. Kellerer","doi":"10.1109/WoWMoM57956.2023.00036","DOIUrl":null,"url":null,"abstract":"Signal quality fluctuates significantly due to blockages of Line of Sight, shadowing, and user mobility. This renders mobility management in 5G quite challenging. To improve it, 3GPP introduced Conditional Handover (CHO), which reduces handover failures by preparing target Base Stations in advance. This algorithm adapts to the varying channel conditions and constantly prepares/releases cells, which leads to an increased exchange of control messages between the user, serving and target BSs. Connecting to the BS with the strongest signal is not always beneficial because available resources and other users’ channels should be considered for a successful network operation. Hence, the need to carefully decide when to hand over, and when that happens, to select the best target BSs. In this paper, we formulate an optimization problem that minimizes the network signaling by reducing the number of unprepared handovers and wasted cell preparations, while providing a minimum rate to everyone. As the problem is NP-hard, we proceed with two approaches. Firstly, we relax it and obtain a lower bound. Secondly, we propose a Cost-Efficient CHO (CECHO) algorithm with performance guarantees. Using 5G trace data, we compare CECHO with two baselines and show that it outperforms them by at least 54% while being near-optimal.","PeriodicalId":132845,"journal":{"name":"2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cost-Efficient Mobility Management in 5G\",\"authors\":\"Anna Prado, Fidan Mehmeti, W. Kellerer\",\"doi\":\"10.1109/WoWMoM57956.2023.00036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Signal quality fluctuates significantly due to blockages of Line of Sight, shadowing, and user mobility. This renders mobility management in 5G quite challenging. To improve it, 3GPP introduced Conditional Handover (CHO), which reduces handover failures by preparing target Base Stations in advance. This algorithm adapts to the varying channel conditions and constantly prepares/releases cells, which leads to an increased exchange of control messages between the user, serving and target BSs. Connecting to the BS with the strongest signal is not always beneficial because available resources and other users’ channels should be considered for a successful network operation. Hence, the need to carefully decide when to hand over, and when that happens, to select the best target BSs. In this paper, we formulate an optimization problem that minimizes the network signaling by reducing the number of unprepared handovers and wasted cell preparations, while providing a minimum rate to everyone. As the problem is NP-hard, we proceed with two approaches. Firstly, we relax it and obtain a lower bound. Secondly, we propose a Cost-Efficient CHO (CECHO) algorithm with performance guarantees. Using 5G trace data, we compare CECHO with two baselines and show that it outperforms them by at least 54% while being near-optimal.\",\"PeriodicalId\":132845,\"journal\":{\"name\":\"2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WoWMoM57956.2023.00036\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WoWMoM57956.2023.00036","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
由于视线、阴影和用户移动性的阻塞,信号质量波动很大。这使得5G的移动性管理非常具有挑战性。为了改进这一点,3GPP引入了条件切换(CHO),通过提前准备目标基站来减少切换失败。该算法适应不同的信道条件,不断地准备/释放单元,从而增加了用户、服务和目标基站之间的控制消息交换。连接到具有最强信号的BS并不总是有益的,因为为了成功的网络操作,应该考虑可用的资源和其他用户的信道。因此,需要仔细决定何时移交,以及何时移交,以选择最佳的目标BSs。在本文中,我们制定了一个优化问题,通过减少未准备的移交和浪费的细胞准备的数量来最小化网络信令,同时为每个人提供最小的速率。由于这个问题是np困难的,我们采用两种方法。首先对其进行松弛,得到一个下界。其次,提出了一种具有性能保证的Cost-Efficient CHO (CECHO)算法。使用5G跟踪数据,我们将CECHO与两条基线进行比较,并表明它在接近最佳的情况下至少比它们高出54%。
Signal quality fluctuates significantly due to blockages of Line of Sight, shadowing, and user mobility. This renders mobility management in 5G quite challenging. To improve it, 3GPP introduced Conditional Handover (CHO), which reduces handover failures by preparing target Base Stations in advance. This algorithm adapts to the varying channel conditions and constantly prepares/releases cells, which leads to an increased exchange of control messages between the user, serving and target BSs. Connecting to the BS with the strongest signal is not always beneficial because available resources and other users’ channels should be considered for a successful network operation. Hence, the need to carefully decide when to hand over, and when that happens, to select the best target BSs. In this paper, we formulate an optimization problem that minimizes the network signaling by reducing the number of unprepared handovers and wasted cell preparations, while providing a minimum rate to everyone. As the problem is NP-hard, we proceed with two approaches. Firstly, we relax it and obtain a lower bound. Secondly, we propose a Cost-Efficient CHO (CECHO) algorithm with performance guarantees. Using 5G trace data, we compare CECHO with two baselines and show that it outperforms them by at least 54% while being near-optimal.