articleIEEE Communications Surveys & TutorialsJan 1, 2019Closed access

Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial

Beijing University of Posts and Telecommunications · Princeton University · +4 more institutions

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Abstract

In order to effectively provide ultra reliable low latency communications and pervasive connectivity for Internet of Things (IoT) devices, next-generation wireless networks can leverage intelligent, data-driven functions enabled by the integration of machine learning (ML) notions across the wireless core and edge infrastructure. In this context, this paper provides a comprehensive tutorial that overviews how artificial neural networks (ANNs)-based ML algorithms can be employed for solving various wireless networking problems. For this purpose, we first present a detailed overview of a number of key types of ANNs that include recurrent, spiking, and deep neural networks, that are pertinent to wireless…

Citation impact

1,093
total citations
FWCI
93.44
Percentile
100%
References
163
Citations per year

Authors

5

Topics & keywords

Keywords
  • Computer science
  • Wireless network
  • Wireless
  • Artificial neural network
  • Leverage (statistics)
  • Context (archaeology)
  • Artificial intelligence
  • Machine learning
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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