Optimizing soft handoff latency and access network selection for next generation mobile communication networks

2016 ◽  
Author(s):  
Moses E. Ekpenyong ◽  
Daniel E. Asuquo ◽  
Etebong B. Isong ◽  
Imeh J. Umoren ◽  
Robinson S. Akpan
Keyword(s):  
Communication Networks ◽  
Mobile Communication ◽  
Access Network ◽  
Network Selection ◽  
Next Generation ◽  
Soft Handoff ◽  
Handoff Latency ◽  
Mobile Communication Networks ◽  
Selection For ◽  
Access Network Selection

scholarly journals Soft Handoff Evaluation and Efficient Access Network Selection in Next Generation Cellular Systems

2017 ◽  
Vol 2 (3) ◽  
pp. 1616-1625
Author(s):  
Moses Ekpenyong ◽  
Daniel Asuquo ◽  
Samuel Robinson ◽  
Imeh Umoren ◽  
Etebong Isong
Keyword(s):  
Access Network ◽  
Cellular Systems ◽  
Network Selection ◽  
Next Generation ◽  
Soft Handoff ◽  
Efficient Access ◽  
Access Network Selection

scholarly journals Data-Driven Handover Optimization in Next Generation Mobile Communication Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Po-Chiang Lin ◽  
Lionel F. Gonzalez Casanova ◽  
Bakary K. S. Fatty
Keyword(s):  
Communication Networks ◽  
Mobile Communication ◽  
Performance Indicator ◽  
Weighted Average ◽  
Data Driven ◽  
Next Generation ◽  
Ping Pong ◽  
Measurement Results ◽  
Mobile Communication Networks ◽  
The Relationship

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.

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