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Self-Adapting Handover Parameters Optimization for SDN-Enabled UDN
DOI:10.1109/TWC.2022.3149415.png)
摘要
En 中文
Increasing the deployment density of small base stations (SBS) is a key method designed to satisfy high data traffic in 5th generation mobile network (5G). However, a large number of SBSs in such ultra-dense network (UDN) may cause ping-pong handovers (HOs), accompanied by increased delay and HO failure. In addition, because of the separation of control and data signaling in 5G, the HO procedure must be performed in both layers. In this paper, we introduce an SDN-based intelligent dynamic HO parameter optimization strategy to minimize both HO failures and ping-pong HOs together. The goal of the proposed strategy is to reduce the HO failure rate and redundant HO (i.e. ping-pong HO) while enabling user equipment (UE) to make full use of the benefits of dense deployment of BSs. Simulation results present that the method proposed in this paper effectively suppresses the ping-pong effect and keeps it at a low level in all of the investigated scenes. In addition, compared with the other algorithms, the HO failure rate is significantly reduced and the throughput of UE is greatly increased, especially in the case of high BS density. Therefore, the benefits of intensive BS deployment are retained.
Keyword:
Optimization
Heuristic algorithms
Throughput
Quality of service
Q-learning
Delays
Sun
Handover
software defined network
hysteresis value
time-to-trigger
self-optimizing
期刊
IF:
10.7
论文数:
1.3W
被引数:
5.3W
机构
引用论文
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Artificial Intelligence-Based Handoff Management for Dense WLANs: A Deep Reinforcement Learning Approach
IEEE ACCESS
IF3.6

