… reinforcement learning techniques. First, we discussed existing surveys then we are focused
on handover (HO) management … Following, this study also discussed how machine learning …

… Handover (HO). HO events become frequent for an ultra-dense dense network scenario, and
HO management … HO control based on the offline reinforcement learning (RL) algorithm that …

… In this work, we have proposed a framework to manage handover events based on multi-agent
deep reinforcement learning. We maximize the average network sum-rate taking into …

… Handovers (HOs) have been envisioned to be more … -wave BSs thereby making HO
management a more crucial task … scheme based on double deep reinforcement learning (DDRL) …

… , and UAV handover management requires a mechanism that … handover decisions. The
UHD is designed to perform efficient handover decisions that eliminate unnecessary handovers …

… , we develop a multi-agent reinforcement learning (MARL) algorithm based on the …
management and power allocation scheme to maximize the throughput while reducing the handover …

… While making handover decisions, it is important to predict … proactive framework wherein
handover timings are optimized … deep reinforcement learning for deciding the handover timings. …

… and discussing mobility and HO management in 5G alongside the … management in 5G
networks accompanied by a discussion on machine learning (ML) applications to HO management…

… management scheme based on deep reinforcement learning, specifically deep Q-network.
The proposed scheme enables the network to learn … “Reducing handover delays for seamless …

… We adopt the reinforcement learning (RL) framework to learn the optimal controller for each
… include energy efficient network management, deep learning, and reinforcement learning. …