A Very Brief Introduction to Machine Learning with Applications to Communication Systems

Osvaldo Simeone

Research output: Contribution to journalArticlepeer-review

329 Scopus citations


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 languageEnglish (US)
Article number8542764
Pages (from-to)648-664
Number of pages17
JournalIEEE Transactions on Cognitive Communications and Networking
Issue number4
StatePublished - Dec 2018

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence


  • Machine learning
  • communication networks
  • supervised learning
  • unsupervised learning
  • wireless communications


Dive into the research topics of 'A Very Brief Introduction to Machine Learning with Applications to Communication Systems'. Together they form a unique fingerprint.

Cite this