Dynamic mobility and handover management in software-defined networking-based fifth-generation heterogeneous networks

被引:4
作者
Khan, Adil [1 ]
Ahmad, Shabeer [2 ]
Ali, Ihsan [3 ]
Hayat, Babar [2 ]
Tian, Yanan [1 ]
Liu, Weixing [1 ]
机构
[1] Xian Eurasia Univ, Sch Informat Engn, Xian, Peoples R China
[2] Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing, Peoples R China
[3] Southeast Missouri State Univ, Dept Comp Sci, Cape Girardeau, MO USA
关键词
handover; HetNets; linear programming; mobility management; multi-attribute decision making; SDN; 5G; SDN;
D O I
10.1002/nem.2268
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The adoption and application of mobile communication technology have rapidly escalated, leading to a significant upsurge in the demand of data traffic. Ultra-densification stands as one of the network solutions within the realm of 5G and beyond technologies, aimed to enhance data rates and network capacity. Heterogeneous networks (HetNets) are deployed with different types of small cells (SCs) in mobile networks to provide high capacity, data rate, throughput, and low latency communication. HetNet solves the problem of network densification at the expense of mobility management problems such as ping-pong handover, unnecessary handovers, handover delay, and cell load. This paper introduces an enhanced optimal cell selection technique employing software-defined networking (SDN) to tackle the challenges of handover and mobility management in 5G and beyond 5G (B5G) HetNet. The proposed SDN-based cell selection scheme leverages linear programming (LP) to manage the mobility of users dynamically, facilitating the selection of the optimal cell for user equipment (UE) handover. This selection is based on multi-attribute decision-making criteria, which include user direction, received signal strength (RSS) value, cell load, and dwell time. By applying LP, computational overhead during cell selection is significantly reduced. The results indicate that the proposed scheme leads to a 39% reduction in number of handovers. This reduction signifies a substantial advancement in mitigating issues associated with frequent and unnecessary handovers, ultimately leading to minimized signaling overhead between UE and cells. Moreover, the proposed solution outperformed the existing scheme in terms of system's throughput and selects an optimal target cell with a lower cell load. This article proposes an optimal next cell selection technique for users in the software-defined heterogeneous network to tackle the challenges of handover and mobility management. The technique uses linear programming (LP) to facilitate optimal cell selection and reduce the number of user handovers based on multiple parameters, including user direction, received signal strength, cell load, and dwell time. image
引用
收藏
页数:18
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