A Machine Learning Approach to User Assignment in 5G Networks

Michael Kouris, Vasileios Kokkinos, Apostolos Gkamas, Philippos Pouyioutas, Christos Bouras

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the advancement of wireless networks the data needs of the wireless internet have become so great, and the use of 4G and 5G so ubiquitous, that challenges arise in the availability and distribution of resources. In this paper we examine an application of Machine Learning and subsequently Neural Networks to offer a solution to this problem. The, now more than ever, profound availability of processing power greatly empowers and makes the deployment of these tools easier than ever, even in problems where in the past their application would not be feasible. The use of machine learning techniques to distribute resources in wireless networks is investigated and contrasted to a traditional algorithmic method. Scenarios are also entertained in which such approaches might be applicable.

Original languageEnglish
Title of host publication2022 Global Information Infrastructure and Networking Symposium, GIIS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages35-39
Number of pages5
ISBN (Electronic)9781665490955
DOIs
Publication statusPublished - 2022
Event2022 Global Information Infrastructure and Networking Symposium, GIIS 2022 - Argostoli, Greece
Duration: 26 Sept 202228 Sept 2022

Publication series

Name2022 Global Information Infrastructure and Networking Symposium, GIIS 2022

Conference

Conference2022 Global Information Infrastructure and Networking Symposium, GIIS 2022
Country/TerritoryGreece
CityArgostoli
Period26/09/2228/09/22

Keywords

  • 5G
  • Deep Learning
  • MIMO
  • Neural Networks
  • User Assignment

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