Abstract
Given the unprecedented availability of data and computing resources, there is widespread renewed interest in applying data-driven machine learning methods to problems for which the development of conventional engineering solutions is challenged by modeling or algorithmic deficiencies. This tutorial-style paper starts by addressing the questions of why and when such techniques can be useful. It then provides a high-level introduction to the basics of supervised and unsupervised learning. For both supervised and unsupervised learning, exemplifying applications to communication networks are discussed by distinguishing tasks carried out at the edge and at the cloud segments of the network at different layers of the protocol stack, with an emphasis on the physical layer.
Original language | English (US) |
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Article number | 8542764 |
Pages (from-to) | 648-664 |
Number of pages | 17 |
Journal | IEEE Transactions on Cognitive Communications and Networking |
Volume | 4 |
Issue number | 4 |
DOIs | |
State | Published - Dec 2018 |
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence
Keywords
- Machine learning
- communication networks
- supervised learning
- unsupervised learning
- wireless communications