… protocol stack (DAPS) handover (HO) is one of the mobility enhancements that can effectively
reduce the handover … a double deep Q-network (DDQN) deep reinforcement learning (DRL…

… framework to learn the optimal handover (HO) controllers in … multi-user deep reinforcement
learning scheme is developed … to frequent handover mitigations in 3gpp mobility protocols,” …

… However, handover policies in current cellular networks are primarily … handover decision
scheme deploying Deep Reinforcement Learning (DRL) to prevent unnecessary handovers …

… 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 (…

… (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 …

… handover (HO) process is determined by the HO events defined in the 3rd Generation Partnership
Project (3GPP) protocol … and some HO parameters defined in protocols, such as time-to…

… handover optimization by using proximal policy optimization in mobile communications to
learn an adaptive handover protocol… the standard 5G NR handover protocol by 3GPP in terms …

… Deep reinforcement learning (DRL), convolutional and deep neural networks received more
… a network layer protocol named radio resource control (RRC) protocol. This protocol is used …

… seamless AP handover protocol and a DRL-based algorithm to constitute an adaptive VLC
handover mechanism for a hybrid 6G network architecture. The proposed protocol can allow …

… We adopt the reinforcement learning (RL) framework to learn the optimal controller for each
… , “A learning approach to frequent handover mitigations in 3gpp mobility protocols,” in IEEE …