… A systematic review is presented in this paper based on QoS parameters in the light of
Machine Learning (ML) techniques. It also provides a methodological framework for the …

… surface (IRS) can reshape the wireless channels by controlling the scattering elements’ …
machine learning (ML) approaches for complex optimization problems in wireless networks. …

… machine learning algorithms for network-wide localization in large wireless sensor networks…
reported work related to localization in wireless sensor networks in the next section. Section …

Machine learning (ML) tasks are becoming ubiquitous in today's network applications.
Federated learning has emerged recently as a technique for training ML models at the …

… This paper compares two machine learning techniques namely: Neural Network (NN) and
Support Vector Machine (SVM), for detecting and counteracting to the DoS attacks launched …

… optimization techniques for RISaided wireless networks, ranging from problem formulations
to … Our work aims to be a roadmap for researchers to optimize RISaided wireless networks. …

… Machine Learning techniques that can be applied on these networks is presented. These …
In context by adopting various Machine Learning techniques in Wireless Sensor Networks we …

… network. Although many approaches exist for addressing the aforementioned challenges, we
… on machine learning solutions3 due to their inherent ability to predict future network states, …

… Machine Learning (ML) for such wireless networks. Every component and building block of
a wireless … our knowledge of wireless technologies up to 5G, such as physical, network and …

… a framework of machine learning based intrusion detection system for wireless sensor
networks. Our system will not be limited on particular attacks, while machine learning algorithm …