… such as vehicular networks, small cell networks and cloud radio access … mobility prediction,
handover parameter optimization, and so on. In this section, machine learning based mobility …

… 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-…

… Cellular-connected UAVs will inevitably be integrated into future cellular networks as
new aerial mobile users. Providing cellular connectivity to UAVs will enable a myriad of …

… Unlike existing RPL based protocols, we introduce a movement prediction of mobile nodes
to mitigate the negative impact of mobility on the network performance. The contribution of …

… First, starting with an overview of mMTC features and QoS provisioning issues, we present
the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of …

… NEXT generation of cellular network technologies is ex- pected to improve … Mobility robustness
optimization (MRO) has been initially … Computer Communications 133, pp. 67-76, 2019. …

… 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-…

… wireless networks are modeled, analyzed, designed, and optimized… optimal cellular network
architecture will be within the context of the emerging fifth generation (5G) wireless networks …