Demo: A Reinforcement Learning-Based Flexible Duplex Systems for B5G with Sub-6 GHz

Soo Min Kim, Han Cha, Seong Lyun Kim, Chan Byoung Chae

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

1 Citation (Scopus)

Abstract

In this paper, we propose a reinforcement learning-based flexible duplex system for B5G with Sub-6 GHz. This system combines full-duplex radios and dynamic spectrum access to maximize the spectral efficiency. We verify this methodâ™s feasibility by implementing an FPGA-based real-time testbed. In addition, we compare the proposed algorithm with the result derived from the numerical analysis through system-level evaluations.

Original languageEnglish
Title of host publication2020 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728151786
DOIs
Publication statusPublished - 2020 Apr
Event2020 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2020 - Seoul, Korea, Republic of
Duration: 2020 May 252020 May 28

Publication series

Name2020 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2020 - Proceedings

Conference

Conference2020 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2020
CountryKorea, Republic of
CitySeoul
Period20/5/2520/5/28

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Instrumentation

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  • Cite this

    Kim, S. M., Cha, H., Kim, S. L., & Chae, C. B. (2020). Demo: A Reinforcement Learning-Based Flexible Duplex Systems for B5G with Sub-6 GHz. In 2020 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2020 - Proceedings [9124745] (2020 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WCNCW48565.2020.9124745