… efficiency in emerging and future cellular networks. Together, … leveraged for choosing optimal
machine learning models for … advanced mobility management framework called Advanced …

… Now we will present some of the research work done on specific machine learning … This
article provides an extensive survey of mobility management for future cellular networks. As …

… optimization problems based on different network structures. Specifically, we mainly focus on
cellular/cell-free networks (… -to-device (D2D) networks (typical applications including power …

… propose a cognitive cellular network (CCN) … cellular networks are introduced in section III.
Also, Section III characterizes the execution of SON functions in the mobility robust optimization …

… network scenarios. This paper aims to provide theoretical foundations for machine learning
and the leading models … for offloading mobile edge-computing decisions based on machine …

… will be available in the future. Figure 1 shows a general 5G cellular network architecture and
the … The state machine of universal mobile telecommunication system (UMTS) technology …

… In light of the existing survey studies, we also identify other potential surveys that could
bridge a gap in a Wireless and Mobile Network setting besides the contents introduced in this …

… and machine learning modelling as well as expert knowledge aided machine learning. …
introduction on modern attacks in mobile networks, ML-based network traffic inspection and real-…

… mobility prediction is the core technology component in designing future mobile communication
network … learning (DL)-based schemes for traffic and mobility prediction by introducing a …

… Cellular networks initiated the fifth generation of cellular … based on a machine learning
model for vehicular fog computing, using a feed-forward neural network to estimate an optimal fog-…