… reinforcement learning, namely RTCP, to alleviate performance degradation problems caused
by handover… This letter strived to answer a critical issue for TCP: How to intelligently adjust …

… [11] applied SDN control functions to achieve intelligent flow control and effective multi-… ,
which achieved optimal distribution of intelligent city applications between MEC servers and …

… two-tier Machine Learning-based scheme for handover management in intelligent vehicular
… of Access Points (APs), to derive a handover trigger decision. In the second tier, a stochastic …

… reinforcement learning (DRL)-based handover scheme by considering multiple handover …
Xu, “QoE-driven intelligent handover for user-centric mobile satellite networks,” IEEE Trans. …

… In this paper, we propose a multiple attributes decision handover strategy jointly … a
caching-aware intelligent handover strategy is given based on the deep reinforcement learning …

… , an intelligent control scheme for a multi-slice RAN. ICRAN leverages deep reinforcement
learning (… Besides this, we redefine handover to include performance triggered handovers. For …

… Therefore, in the next chapter, we propose a reinforcement learning-based intelligent
handover algorithm to simultaneously optimize the three constraints modeled in Section II. …

… challenges to the handover algorithm. This paper designs a reinforcement learning-based …
QoE-driven intelligent handover for user-centric mobile satellite networks[J]. IEEE …

… network-based and MS-based handover approaches are adaptively considered to find an
optimal handover policy; (2) to determine the WLAN handover policy, we considered not only …

… ), a novel intelligent handover algorithm based on deep reinforcement learning (DRL), …
process (MDP) and enables network to dynamically handover according to current network states. …