… efficient way to reduce the channel scanning procedure for fast handover. … management
has recently been introduced for mobility support in enterprise WLANs, virtual AP management …

… ML algorithms are classified as supervised, unsupervised, and reinforcement learning.
For more detailed information about ML, the referenced resources can be viewed. …

… In this paper, we propose a novel vertical handover mechanism that considers QoE prediction
… The reinforcement learning is more complex and needs a huge number of samples and …

… In traditional handover scheme, When RSSI between STA and AP is lower than threshold,
handover is … interfaces that administrators can control and manage network through it [3, 4]. …

… uses reinforcement learning techniques and inter-cell coordination for improving the handover
… reinforcement learning techniques in this paper, as will be discussed in Sections 3 and 3. …

… The training data is the input of the proposed handover management algorithm to train the
policy in the second part. After that, the validation data can be used to verify the performance …

… between handover paths and learns the user flow among cells by using the handover and
load … In our model, reinforcement learning agents are placed on base stations and work in a …

… Handover management is one of the challenges, which has become one of the main
barriers to overall network performance. During the movement of user equipment (UE), the UE …

… concept of coordinated machine learning for handover of users and … reinforcement learning
(DRL) for an adjustment of handover … Like in the related works on handover management, we …

… handover management related issues. In [11], the authors proposed a Deep Reinforcement
Learning … • We introduce a novel handover management architecture that can be deployed in …