Towards coexistence of cellular and WiFi networks in unlicensed spectrum: A neural networks based approach

Madyan Alsenwi, Ibrar Yaqoob, Shashi Raj Pandey, Yan Kyaw Tun, Anupam Kumar Bairagi, Lok Won Kim, Choong Seon Hong

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Long-Term Evolution in the Unlicensed Spectrum (LTE-U) is considered as an indispensable technology 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 raise the need to derive an efficient and fair coexistence mechanism among different radio access networks. In this paper, we propose a novel mechanism based on neural networks for the coexistence of an LTE-U BS in the unlicensed spectrum alongside with WiFi access points. Specifically, we model the problem in coexistence as a 2-Dimensions Hopfield Neural Network (2D-HNN) based optimization problem that aims to achieve fairness considering both the LTE-U data rate and the QoS requirements of WiFi networks. Using the energy function of 2D-HNNs, precise investigation of its minimization property can directly provide the solution of the optimization problem. Furthermore, the problem of allocating the unlicensed resources to LTE-U users is modeled as a 2D-HNN and its energy function is leveraged to allocate resources to LTE-U users based on their channel states. Numerical results show that the proposed algorithm allows the LTE-U BS to work efficiently in the unlicensed spectrum while protecting the WiFi networks. Moreover, more than 90% fairness among the LTE-U users is achieved when allocating the unlicensed resources to LTE-U users based on the proposed algorithm.

Original languageBritish English
Article number2933323
Pages (from-to)110023-110034
Number of pages12
JournalIEEE Access
Volume7
DOIs
StatePublished - 2019

Keywords

  • 5G wireless networks
  • Hopfield neural networks
  • LTE-U
  • Proportional fair
  • Resource allocation
  • WiFi

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