… 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 …

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

… aim to establish an HO management and power allocation scheme to maximize the throughput
while reducing the handover frequency. We model the multipleUE handover and power …

… 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 …

… In this paper, we first design a self-learning architecture applicable to the SDN-based WLAN
… handoff management scheme based on deep reinforcement learning, specifically deep Q-…

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

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

… which are delivered to the RLC layer before the Handover Success. Therefore, the UE can
receive … First, the T-gNB sends a Path Switch Request to the access and mobility management …

… deep reinforcement learning framework based on the Actor − Critic method to deal with the
wireless handover … computing environment to learn the optimal wireless handover policy. …