… Considering that it’s hard to perceive accurate and complete CSI of HSR environment, we
developed a novel deep reinforcement learning framework, termed as LSTM-DDPG, which …

… load balancing and frequent handovers in the massive base station (BS) deployment. In this
paper, an intelligent user access control scheme with deep reinforcement learning (DRL) is …

… In this paper, we proposed a new method for managing the handover in heterogeneous
5G mobile networks based on artificial intelligence technologies by using recurrent neural …

… Conclusion In this paper, we proposed a deep reinforcement learning-based approach
for joint server selection, cooperative offloading and handover in multi-access edge wireless …

… In this paper, we propose an optimal intelligent VHO algorithm of multi-criteria called MCIHO…
method and deep reinforcement learning, to tackle the problems regarding handover failure, …

… Abstract—In this paper, we apply reconfigurable intelligent surface (RIS) technique to aid …
then propose an efficient algorithm based on deep reinforcement learning (DRL), namely deep …

… propose a deep reinforcement learning framework to overcome dynamic blockage. By
dynamically adjusting blockage detection parameters and making intelligent handover decisions …

… 5G or high level intelligent assisted driving applications. The … focus on the serving handover
between the adjacent RSUs. … scheme based on deep reinforcement learning (DRL), while …

… a handover approach based on reinforcement learning in [6]. The method services a centralized
reinforcement learning … towards govern an optimal handover selection to optimize long-…

… ) selection method for proactive decision handover (HO) in … a solution based on Reinforcement
Learning (RL) framework. … The numerical results show that the intelligent, learned agent …