… intelligent transportation, and so on. This has … learning, which refers to the deployment of
machine learning algorithms (including supervised, unsupervised, and reinforcement learning) …

… intelligent communications. In our discussion, we consider different subcategories of machine
learning … , Bayesian learning, k-means clustering, principal component analysis, and Q-…

… Machine learning algorithms facilitate complicated scenarios … of machine learning algorithms
into communication systems will improve the QoS and make the systems smart, intelligent, …

… problems in IoT wireless communications with an emphasis on … machine learning techniques.
Then, by adopting a bottom-up approach, we examine existing work on machine learning …

… wireless communication … learning (DL)-based IRS-enhanced communication. We focus on
their operating principles, channel estimation (CE), and the applications of machine learning …

… -based communication-efficient federated machine learning … model aggregation of federated
machine learning. We discuss … communication-efficient federated machine learning. Finally, …

… The scenario identification concerned in this paper belongs to the supervised learning in
machine learning. Supervised learning means that each input vector in the training datasets …

… We introduce the machine learning based network access in terms of the three aspects in …
machine learning based routing approaches are investigated in terms of the different learning …

… , 6G networks need to transform to a unified communication, sensing, and computing platform
incorporating artificial intelligence and machine learning methodologies [9]. This platform …

… communications and networking, to discuss open issues related to the application of machine
learning … share new ideas and techniques for big data analysis in communication systems. …