Decentralized Deep Reinforcement Learning-based Dynamic Uplink Band Selection in Enhanced Licensed-Assisted Access

Fitsum Debebe Tilahun, Chung G. Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Enhanced licensed-assisted access (eLAA) is an operational mode that allows the use of unlicensed band to support long-term evolution (LTE) service via carrier aggregation technology. The extension of additional bandwidth is beneficial to meet the demands of the growing mobile traffic. In the uplink eLAA, which is prone to unexpected interference from WiFi access points, resource scheduling by the base station, and then performing listen-before-talk by the users can seriously affect the resource utilization. In this paper, we present a decentralized deep reinforcement learning (DRL)-based approach in which each user independently learns dynamic band selection strategy that maximizes its own rate. Through extensive simulations, we showed that the proposed DRL-based band selection scheme not only improves resource utilization, but also guarantee certain minimum Quality of Service (QoS).

Original languageEnglish
Title of host publication34th International Conference on Information Networking, ICOIN 2020
PublisherIEEE Computer Society
Pages477-480
Number of pages4
ISBN (Electronic)9781728141985
DOIs
Publication statusPublished - 2020 Jan
Event34th International Conference on Information Networking, ICOIN 2020 - Barcelona, Spain
Duration: 2020 Jan 72020 Jan 10

Publication series

NameInternational Conference on Information Networking
Volume2020-January
ISSN (Print)1976-7684

Conference

Conference34th International Conference on Information Networking, ICOIN 2020
CountrySpain
CityBarcelona
Period20/1/720/1/10

Keywords

  • deep reinforcement learning (DRL)
  • dynamic band selection
  • enhanced licensed-assisted access (eLAA)
  • long short-term memory (LSTM)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Tilahun, F. D., & Kang, C. G. (2020). Decentralized Deep Reinforcement Learning-based Dynamic Uplink Band Selection in Enhanced Licensed-Assisted Access. In 34th International Conference on Information Networking, ICOIN 2020 (pp. 477-480). [9016460] (International Conference on Information Networking; Vol. 2020-January). IEEE Computer Society. https://doi.org/10.1109/ICOIN48656.2020.9016460