A Hopfield Neural Networks Based Mechanism for Coexistence of LTE-U and WiFi Networks in Unlicensed Spectrum

Madyan Alsenwi, Yan Kyaw Tun, Shashi Raj Pandey, Choong Seon Hong

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

2 Citations (Scopus)

Abstract

Long-Term Evolution in the unlicensed spectrum (LTE-U) is considered as an indispensable technique to mitigate the spectrum scarcity in wireless networks. Typical LTE transmissions are contention-free and centrally controlled by the base station (BS); however, the wireless networks that work in unlicensed bands use contention-based protocols for channel access, which raises the need to derive an efficient and fair coexistence mechanism among different radio access networks. In this work, we propose a novel neural networks (NNs) based mechanism for the coexistence of an LTE-U base station (BS) in the unlicensed spectrum alongside with a WiFi access point (WAP). Specifically, we model the coexistence problem as a Hopfield Neural Network (HNN) based optimization problem that aims a fair coexistence considering both the LTE-U data rate and the QoS requirements of the WiFi network. Using the energy function of HNN, precise investigation of its minimization property can directly provide the solution of the optimization problem. Numerical results show that the proposed mechanism allows the LTE-U BS to work efficiently in the unlicensed spectrum while protecting the WiFi network.

Original languageEnglish
Title of host publication2019 20th Asia-Pacific Network Operations and Management Symposium
Subtitle of host publicationManagement in a Cyber-Physical World, APNOMS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9784885523205
DOIs
Publication statusPublished - Sept 2019
Event20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019 - Matsue, Japan
Duration: 18 Sept 201920 Sept 2019

Publication series

Name2019 20th Asia-Pacific Network Operations and Management Symposium: Management in a Cyber-Physical World, APNOMS 2019

Conference

Conference20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019
Country/TerritoryJapan
CityMatsue
Period18/09/1920/09/19

Bibliographical note

Publisher Copyright:
© 2019 IEICE.

Keywords

  • LTE-U
  • coexistence
  • hopfield neural networks (HNNs)
  • resource allocation

Fingerprint

Dive into the research topics of 'A Hopfield Neural Networks Based Mechanism for Coexistence of LTE-U and WiFi Networks in Unlicensed Spectrum'. Together they form a unique fingerprint.

Cite this