… Channel modeling is fundamental to design wireless … time, machine learning has been
successfully demonstrated efficient handling big data. In this paper, applying machine learning to …

… of machine learning techniques to the improvement of the congestion control of TCP in
wired/wireless networks. TCP is suboptimal in hybrid wired/wireless networks because it reacts in …

… machine learning algorithms to detect anomalous readings in medical WSNs. We will compare
the performance of different machine learning … detection and machine learning algorithms …

… Hence, our focus is on the comprehensive survey of machine learning aided … of machine
learning aided wireless networks. We commence by investigating a series of popular learning …

… potentiality of regression-based machine learning algorithms for estimating the node
localisation error. The key objective of regressionbased machine learning algorithms is to predict …

… in wireless sensor networks by combining machine learning and Kalman filtering. For the
learning process, we investigated the use of two kernel-based machine learning algorithms: …

… cabling (such as optical fibres) or wireless media may be used to convey the information or
resources (such as Wi-Fi). Using computer networks, users may access the World Wide Web, …

… Instead here we also discuss the role machine learning, in the form of model-based and …
end learning and physics-based learning, can play to design future wireless-powered networks. …

… This study presents a 5G network architecture and next-generation wireless networks (NGWN)
communication architecture model. Besides this, we also present 3GPP-based physical …

… In this paper, we have presented a survey of the different machine learning algorithms
used to secure WSNs and IoT. Table I summarizes the different machine learning approaches …