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強化学習を用いた広帯域ミリ波最適スペクトル制御と先験知識を予測する技術の開発

Research Project

Project/Area Number 20J12528
Research Category

Grant-in-Aid for JSPS Fellows

Allocation TypeSingle-year Grants
Section国内
Review Section Basic Section 60010:Theory of informatics-related
Research InstitutionKeio University

Principal Investigator

曹 誉文  慶應義塾大学, 理工学部, 特別研究員(PD)

Project Period (FY) 2020-04-24 – 2022-03-31
Project Status Discontinued (Fiscal Year 2021)
Budget Amount *help
¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 2021: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2020: ¥900,000 (Direct Cost: ¥900,000)
KeywordsDeep learning / Resource allocation / Network control / Mobile edge computing / Analog beamforming / mmWave communications / deep learning / routing / caching / dense networks / federated learning
Outline of Research at the Start

This research focuses on developing innovative spectrum resource allocation and electromagnetic radiation pattern predicting algorithms for 28 GHz mmWave channels. This research will find new technologies that can be utilized in mmWave or Terahertz band communications, and tackle some open problems.

Outline of Annual Research Achievements

In this research-year, I focuse mainly on the following two research-topics: 1>. Low-overhead beam and power resource allocation using deep learning and its application in multiuser millimeter-wave (mmWave) communications; 2>. Deep learning-based network control and management in mobile edge computing (MEC) systems. Related research results have been published in high-quality journal and conference papers, respectively. Throughout our experiments, I generate images of resolution 4×4 and 8×8 and use these for distance estimation between users. Afterwards, I apply super resolution on images with size 4×4 to improve their resolution, and compare their results to the ones obtained with the original 8×8 images. For an area roughly equal to 60×30m, the proposed approach reaches an average mean squared error equal to 0.13 m.

Research Progress Status

令和3年度が最終年度であるため、記入しない。

Strategy for Future Research Activity

令和3年度が最終年度であるため、記入しない。

Report

(2 results)
  • 2021 Annual Research Report
  • 2020 Annual Research Report
  • Research Products

    (13 results)

All 2022 2021 2020 Other

All Int'l Joint Research (4 results) Journal Article (4 results) (of which Peer Reviewed: 4 results) Presentation (5 results) (of which Int'l Joint Research: 1 results)

  • [Int'l Joint Research] University of Tubingen(ドイツ)

    • Related Report
      2021 Annual Research Report
  • [Int'l Joint Research] SUTD(シンガポール)

    • Related Report
      2021 Annual Research Report
  • [Int'l Joint Research] University of Tubingen(ドイツ)

    • Related Report
      2020 Annual Research Report
  • [Int'l Joint Research] SUTD(シンガポール)

    • Related Report
      2020 Annual Research Report
  • [Journal Article] Mobility-Aware Routing and Caching in Small Cell Networks using Federated Learning2022

    • Author(s)
      Yuwen Cao, Setareh Maghsudi, Tomoaki Ohtsuki
    • Journal Title

      Arxiv

      Volume: 1 Pages: 1-29

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Spatial Degrees of Freedom Exploration and Analog Beamforming Designs for Signature Spatial Modulation2021

    • Author(s)
      CAO Yuwen、OHTSUKI Tomoaki
    • Journal Title

      IEICE Transactions on Communications

      Volume: E104.B Issue: 8 Pages: 934-941

    • DOI

      10.1587/transcom.2020EBT0010

    • NAID

      130008070236

    • ISSN
      0916-8516, 1745-1345
    • Year and Date
      2021-08-01
    • Related Report
      2020 Annual Research Report
    • Peer Reviewed
  • [Journal Article] A Deep Learning-based Low Overhead Beam Selection in mmWave Communications2021

    • Author(s)
      H. Echigo, Y. Cao, M. Bouazizi, and T. Ohtsuki
    • Journal Title

      IEEE Trans. on Vehicular Technology

      Volume: 70 Issue: 1 Pages: 682-691

    • DOI

      10.1109/tvt.2021.3049380

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Dual-Ascent Inspired Transmit Precoding for Evolving Multiple-Access Spatial Modulation2020

    • Author(s)
      Cao Yuwen、Ohtsuki Tomoaki、Quek Tony Q. S.
    • Journal Title

      IEEE Transactions on Communications

      Volume: 68 Issue: 11 Pages: 6945-6961

    • DOI

      10.1109/tcomm.2020.3013030

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed
  • [Presentation] Low-overhead Beam and Power Allocation Using Deep Learning for mmWave2022

    • Author(s)
      Yuwen Cao and Tomoaki Ohtsuki
    • Organizer
      無線通信システム研究会(RCS)
    • Related Report
      2021 Annual Research Report
  • [Presentation] A Novel Approach for Inter-User Distance Estimation in 5G mmWave Networks Using Deep Learning2021

    • Author(s)
      Mondher Bouazizi, Siyuan Yang, Yuwen Cao, Tomoaki Ohtsuki
    • Organizer
      2021 26th IEEE Asia-Pacific Conference on Communications (APCC), 2021
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Mobility Aware Routing and Caching: A Federated Learning Assisted Approach2021

    • Author(s)
      Yuwen Cao, Setareh Maghsudi, and Tomoaki Ohtsuki
    • Organizer
      IEEE Conference on Communications (ICC), 2021, (国際学会)
    • Related Report
      2020 Annual Research Report
  • [Presentation] Mobility Aware Routing and Caching in 5G Ultra Dense Networks2020

    • Author(s)
      Yuwen Cao and Tomoaki Ohtsuki
    • Organizer
      無線通信システム研究会(RCS)
    • Related Report
      2020 Annual Research Report
  • [Presentation] Multi Configuration Selection Mechanisms and Analog Precoding for Signature Spatial Modulation2020

    • Author(s)
      Yuwen Cao and Tomoaki Ohtsuki
    • Organizer
      IEEE Conference on Communications (ICC) (Virtual Conference), 2020
    • Related Report
      2020 Annual Research Report

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Published: 2020-07-07   Modified: 2024-03-26  

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