… -tier Machine Learning-based scheme for handover management in … handover management
protocol using the previously derived LSTM model. The proposed handover management …

… trajectory designs, resource management, energy efficiency and handover control. So far, …
Reinforcement learning based predictive handover for pedestrian-aware mmwave networks …

… This is due to the fact that we perform load balancing by triggering the handover procedure.
As the cell-edge users suffer from high levels of interference and low signal power, low SINR …

… challenges to the handover algorithm. This paper designs a reinforcement learning-based
multi-… This paper mainly studies the handover management function in mobility management. …

… management issue in real heterogeneous networks consisting of admission control, access
network selection and vertical handover … system using reinforcement learning without state …

… -based Intelligent Mobility Management (LIM2), for mobility management in 5G and beyond,
… the handover using state-action-reward-state-action (SARSA)-based reinforcement learning, …

… In this work, a deep reinforcement learning method was proposed to provide a centralized
control of multiple users in order to enhance the data rate and avoid unnecessary …

… The applications should be implemented by relevant ML algorithms, such as Reinforcement
learning, decision tree, logistic regression, Neural networks (NN), Bayesian network (BN), …

… Therefore, we apply deep reinforcement learning to further enhance the risk management
in … In this paper, we study the mobility management problem for the handover in MEC and …

… 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. …