… A brief overview of, the evolution of the cellular technologies, network configurations, handover,
edge computing and deep learning will be discussed in this Chapter. Subsection 2.4 will …

… utilizing deep learning methods in the UWSN handover prediction task. This is because
the performance of the deep-learning-based models outperform the classic machine-learning-…

… To reduce the HO failure rate and decrease the HIT in 5G mm-Wave network, Baik and others
in [29] proposed a HO scheme based on deep learning that uses soft HO, multi connectivity…

… It is obvious that the SINR-based HO induces more handover since, at each attachment to
a … On the other hand, using the DDPG only handover and our proposed HO scheme, fewer …

… a cell i referred to as ℘i and handover margin of a cell i referred to … and handover settings of
a cluster of LTE cell towers min- … First, we propose a deep learning scheme that identifies the …

… The utilization of deep learning in such a system allows for … Our approach on handover
optimization is purely non-… In this paper, we propose a deep learning-based positioning algorithm …

… deep Q-learning (SDQL) algorithm to make the handover decision in the distributed scheme.
The developed algorithm … In the decision phase, each user makes their handover decision …

… such as handover thresholds and handover neighbor lists are the … ML algorithms for decision
making are dynamic ML algorithms … networks, reinforcement learning, and deep learning. …

… In this paper, we present a deep learning framework for the prediction of … deep-learning
(DL) models provide a sense of surroundings to the BSs, thereby enabling proactive handover (…

… handover is a new direction. Recently, we introduced a paradigm called the deep RLbased
image-to-decision proactive handover … handover decision without explicitly estimating the po- …