Data-Driven Handover Optimization in Next Generation Mobile Communication Networks
Network densification is regarded as one of the important ingredients to increase capacity for next generation mobile communication networks. However, it also leads to mobility problems since users are more likely to hand over to another cell in dense or even ultradense mobile communication networks...
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Hindawi Limited
2016-01-01
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Series: | Mobile Information Systems |
Online Access: | http://dx.doi.org/10.1155/2016/2368427 |
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doaj-30b5230aa3ec4e238c828e71a50510f72021-07-02T04:49:40ZengHindawi LimitedMobile Information Systems1574-017X1875-905X2016-01-01201610.1155/2016/23684272368427Data-Driven Handover Optimization in Next Generation Mobile Communication NetworksPo-Chiang Lin0Lionel F. Gonzalez Casanova1Bakary K. S. Fatty2Department of Communications Engineering, Yuan Ze University, Taoyuan 320, TaiwanDepartment of Communications Engineering, Yuan Ze University, Taoyuan 320, TaiwanDepartment of Communications Engineering, Yuan Ze University, Taoyuan 320, TaiwanNetwork densification is regarded as one of the important ingredients to increase capacity for next generation mobile communication networks. However, it also leads to mobility problems since users are more likely to hand over to another cell in dense or even ultradense mobile communication networks. Therefore, supporting seamless and robust connectivity through such networks becomes a very important issue. In this paper, we investigate handover (HO) optimization in next generation mobile communication networks. We propose a data-driven handover optimization (DHO) approach, which aims to mitigate mobility problems including too-late HO, too-early HO, HO to wrong cell, ping-pong HO, and unnecessary HO. The key performance indicator (KPI) is defined as the weighted average of the ratios of these mobility problems. The DHO approach collects data from the mobile communication measurement results and provides a model to estimate the relationship between the KPI and features from the collected dataset. Based on the model, the handover parameters, including the handover margin and time-to-trigger, are optimized to minimize the KPI. Simulation results show that the proposed DHO approach could effectively mitigate mobility problems.http://dx.doi.org/10.1155/2016/2368427 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Po-Chiang Lin Lionel F. Gonzalez Casanova Bakary K. S. Fatty |
spellingShingle |
Po-Chiang Lin Lionel F. Gonzalez Casanova Bakary K. S. Fatty Data-Driven Handover Optimization in Next Generation Mobile Communication Networks Mobile Information Systems |
author_facet |
Po-Chiang Lin Lionel F. Gonzalez Casanova Bakary K. S. Fatty |
author_sort |
Po-Chiang Lin |
title |
Data-Driven Handover Optimization in Next Generation Mobile Communication Networks |
title_short |
Data-Driven Handover Optimization in Next Generation Mobile Communication Networks |
title_full |
Data-Driven Handover Optimization in Next Generation Mobile Communication Networks |
title_fullStr |
Data-Driven Handover Optimization in Next Generation Mobile Communication Networks |
title_full_unstemmed |
Data-Driven Handover Optimization in Next Generation Mobile Communication Networks |
title_sort |
data-driven handover optimization in next generation mobile communication networks |
publisher |
Hindawi Limited |
series |
Mobile Information Systems |
issn |
1574-017X 1875-905X |
publishDate |
2016-01-01 |
description |
Network densification is regarded as one of the important ingredients to increase capacity for next generation mobile communication networks. However, it also leads to mobility problems since users are more likely to hand over to another cell in dense or even ultradense mobile communication networks. Therefore, supporting seamless and robust connectivity through such networks becomes a very important issue. In this paper, we investigate handover (HO) optimization in next generation mobile communication networks. We propose a data-driven handover optimization (DHO) approach, which aims to mitigate mobility problems including too-late HO, too-early HO, HO to wrong cell, ping-pong HO, and unnecessary HO. The key performance indicator (KPI) is defined as the weighted average of the ratios of these mobility problems. The DHO approach collects data from the mobile communication measurement results and provides a model to estimate the relationship between the KPI and features from the collected dataset. Based on the model, the handover parameters, including the handover margin and time-to-trigger, are optimized to minimize the KPI. Simulation results show that the proposed DHO approach could effectively mitigate mobility problems. |
url |
http://dx.doi.org/10.1155/2016/2368427 |
work_keys_str_mv |
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1721339434790551552 |