Optimizing handover decisions with skipping mechanisms in 5G mmWave UDNs using reinforcement learning

Key Points

• Optimizing handover decisions improves connectivity in 5G mmWave ultra-dense networks.
• A significant enhancement of 25% was observed in decision-making efficiency through reinforcement learning.
• Analysis of handover scenarios using skipping mechanisms showed improved metrics and reduced latency.
• This indicates the potential for better performance in high-density environments and necessitates further in-field testing.