… presents a handover optimization scheme that integrates deep reinforcement learning (DRL) …
[29] proposed an intelligent handover strategy employing a multi-attribute graph (MAG) and …

… In a HetNet, handover and power allocation were controlled using a Multi-Agent Reinforcement
Learning (… Zhang, and MA Imran, “Intelligent handover algorithm for vehicle-to-network …

… How can a handover method be designed to … a learning-based handover method based
on keeping an updated backup channel for the serving BS. We use reinforcement learning (RL) …

… used handover algorithm and an Reinforcement Learning (RL)-based handover algorithm,
… Hence, an intelligent approach is required to decide if a handover should be triggered or not…

… In this paper, we propose a multi-agent deep reinforcement learning (MADRL) based
autonomous channel selection and transmission power selection algorithm for T2T communication …

… problems of frequent handover and large overheads for positioning in 6G, this paper proposes
a reinforcement learning (RL)-based visible light positioning (VLP) handover scheme by …

… This leads to an increased number of handovers of user … for handover optimization by
using proximal policy optimization in mobile communications to learn an adaptive handover …

… Recently, the reinforcement learning (RL) algorithm, which is commonly employed in the …
intelligence, was introduced to develop an optimal handover scheme through the learning …

… on Reinforcement Learning Reinforcement Learning (RL) is a field in machine learning
that … framework more agile, we designed an intelligent learning architecture for the SDN-enabled …

… Reinforcement Learning-Based Handover In this section, we introduce the Reinforcement
Learningbased Handover (RLHO) algorithm, which is a multi-criteria HO algorithm that takes …