… based on the offline reinforcement learning (RL) algorithm that … Therefore, in this paper, we
present an intelligent method … Section III, the Deep Reinforcement Learning (DRL) framework …

… ability of reinforcement learning, this paper proposes an adaptive optimization method based
on the Q-Learning algorithm to achieve real-time estimation of the handover parameters of …

… These traditional methods without artificial intelligence (AI) … handover mechanisms; in
particular, reinforcement learning (RL) algorithms have been applied in AP selection and handover …

… method for handover optimization in a 5G cellular network using reinforcement learning (RL).
In contrast to the conventional method, we propose to control the handovers between base-…

… To this end, we propose a QoE-driven intelligent handover … ; To improve the effectiveness
of handover, an available channel … a reinforcement learning method to build the handover …

… , especially handover decisions. With the rapid development of … learning, reinforcement
learning (RL), such as Q-learning and deep Q-network (DQN), has been applied to handover …

… 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 (…

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