… is to resort to advanced machine learning techniques, in order … The recent success of deep
learning underpins new and … gap between deep learning and mobile and wireless networking …

… With the growth of mobile technology in the last decade, wireless networks have become
an integral part of our everyday lives. To meet the increasingly stringent application …

… deep neural network to tolerate missing or distorted input data. This capability is important to
wireless networks … due to the channel fading, node mobility, and control channel failure. (2) …

… of machine learning and deep learning in wireless networks. Due to the dynamic behaviour
of network scenarios in several adhoc networks (… and mobility of nodes in wireless networks, …

… and mobile applications, wireless network optimization has seen a tremendous increase in
… to exploit deep learning for significant performance gain in wireless network optimization. …

… Similarly, a standardization initiative for machine learning in future mobile networks has …
framework for machine learning in future networks, defining the integration of machine learning …

… popular machine learning techniques utilized in wireless networks, … The applications of
machine learning in resource management are … In this section, machine learning based mobility …

… , next-generation wireless networks can leverage intelligent, … of machine learning (ML) notions
across the wireless core and … recent wireless networking paradigms, such as mobile edge …

… recent wireless networking paradigms such as mobile edge … the topic of machine learning
for wireless network design. The … , from machine learning and wireless communications, that …

… (3) “A fusion optimization algorithm of network element layout for indoor positioning,” by Xiao…
]; (4) “A 3D mobile positioning method based on deep learning for hospital applications,” by …