… network slicing using deep reinforcement learning to support the space-air-ground integrated
networks … Specifically, we propose a reinforcement learning model with specific designs of …

… This article proposes an approach … for network slicing in the 5G core network. The admission
control mechanism introduces two solutions, one based on reinforcement learning (called …

… The role of the FlexRAN controller in our network slicing system is to slice the RAN by
getting the network slice template from the IBN component RAN slicing configurator. The …

… network slices, we consider the numerology, bandwidth, and transmit power used by each
network slice as … The service provider determines the configuration parameters for the network …

… We study a scenario composed of a single CU connected to a set of RRHs from 4 to 16 (R =
4 to R = 16) and adopt the values of [38]–[40] to define three types of applications, ie, medical…

… consider a multi-agent learning method that can observe the dynamic environment and
learn the strategies of other agents. Policy-based methods eg DDPG learn stochastic strategies …

… To this end, the ability to predict the actual footprint of a particular network slice is essential
… three key network slicing building blocks: i) a forecasting module that predicts network slices…

… via network slicing. Furthermore, integration challenges and open research problems related
to the network slicing in … /Machine Learning (AI/ML) in network slicing and IoT integration. …

… network slicing in detail, there is no comprehensive study … Furthermore, we discuss key
requirements for network slicing to enable … along with possible guidelines for network slicing. …

… network slicing based on software-defined networking (SDN), where an SDN controller controls
the network slicing … ) process with the help of the slice manager. The considered problem …