… to perform a handover predictively using … handover, this paper presents a reinforcement
learning framework. The important point in this framework is learning the optimal handover …

… Most of these works use Reinforcement Learning (RL) ML techniques, in which a model is
trained online during interaction with environment, without the need for prepared training data. …

… In this paper, we propose a Deep Reinforcement Learning (DRL)-based UAV handover
decision (UHD) scheme that overcomes the limitations in the aforementioned studies. A UHD …

… use a deep reinforcement learning for deciding the handover … space facilitates (i) the prediction
of obstacle-caused data rate … to a handover framework without the state space expansion. …

… (BS) in the process, commonly known as Handover (HO). HO events become frequent for an
… In this study, we propose a model for HO control based on the offline reinforcement learning …

… using reinforcement learning (RL). In contrast to the conventional method, we propose to
control the handovers … systems based on channel blockage prediction. In [10], authors propose …

… Handovers (HOs) have been envisioned to be more challenging in 5G networks due to the
… In this paper, we propose an offline scheme based on double deep reinforcement learning (…

… In the following, we propose a solution based on multi-agent reinforcement learning to … a
framework to manage handover events based on multi-agent deep reinforcement learning. We …

In this paper, we study the handover (HO), and power allocation problem in a two-tier … UE,
we develop a multi-agent reinforcement learning (MARL) algorithm based on the proximal …

… a Deep Reinforcement Learning (DRL) … handover procedure in 3GPP, and introduces
the handover types in an O-RAN environment. Section III presents our predictive handover …