… reinforcement learning, which is referred to as HSR-CC, to alleviate performance degradation
problems induced by handover. … Collaboration: This architecture is good for the intelligent …

… two parts: intelligent handover trigger condition and optimal handover decision. Specifically,
we use MAPPO algorithm to learn the HO trigger condition in the intelligent handover trigger …

… In the recent past, 5G mobility management has been explored with machine and artificial
intelligence (AI) learning solutions. Some of these include deep and reinforcement learning (…

… and propose a centralized adaptive intelligent handover mechanism for LEO megaconstellations,
where the handover delay and handover failure probability are jointly considered. Then…

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

… , an intelligent control scheme for a multi-slice RAN. ICRAN leverages deep reinforcement
learning (… Besides this, we redefine handover to include performance triggered handovers. For …

… [11] applied SDN control functions to achieve intelligent flow control and effective multi-… ,
which achieved optimal distribution of intelligent city applications between MEC servers and …

… two-tier Machine Learning-based scheme for handover management in intelligent vehicular
… of Access Points (APs), to derive a handover trigger decision. In the second tier, a stochastic …

… facilitate the exploitation versus exploration tradeoff to accelerate the learning. We adopt
the reinforcement learning (RL) framework to learn the optimal controller for each UE, which …

… reinforcement learning (DRL)-based handover scheme by considering multiple handover …
Xu, “QoE-driven intelligent handover for user-centric mobile satellite networks,” IEEE Trans. …