… and wireless networks. We have provided a brief discussion on the various ML modalities,
application of machine learning in wireless networks and … on machine learning applications. …

… networks (SON) solutions and provides, not only an overview of the most common ML techniques
encountered in cellular networks … the application of ML algorithms in cellular networks, …

… with deep learning AI … wireless network service providers to (i) offer high automation levels
from distributed AI/ML architectures applicable at the network edge, (ii) implement application-…

… in various areas including wireless networking. While existing deep learning applications
mainly focus … research issues in wireless networks is yet to be explored. With the proliferation of …

… such as the physical layer, medium access layer, and application layer. Zero-touch optimization
of wireless networks using ML is another interesting aspect that is discussed in this paper…

… of uses cases, including mobile broadband, tactile Internet, device-to-device communications,
and unmanned aerial vehicles. In addition, we present a deep reinforcementlearning-…

… In this article, we comprehensively review the applications of RL in wireless networks from
a layering perspective. First, we present an overview of the principle, fundamentals, and sev…

… networks This article applies RL to achieve context awareness and intelligence in wireless
networks. RL is a simple and model-free approach, and this implies two characteristics. Firstly…

… In this work, we first outline existing applications of Machine Learning in the communications
domain and further list the most significant challenges and potential solutions while …

… Our approach is datadriven and borrows machine learning tools to determine an accurate
… We consider a cellular network where the base stations (BS) are randomly distributed on the …