Joint Communication and Computing Resource Allocation over Cell-Free Massive MIMO-enabled Mobile Edge Network: A Deep Reinforcement Learning-based Approach

Fitsum Debebe Tilahun, Ameha Tsegaye Abebe, Chung G. Kang

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

    5 Citations (Scopus)

    Abstract

    We present a cell-free massive MIMO-enabled mo-edge network with the aim of meeting the stringent rements of the newly introduced multimedia services. For considered framework, we propose a distributed deep-orcement learning (DRL)-based joint communication and uting resource allocation wherein each user is implemented n independent agent to make joint resource allocation ion relying on local observation only. The simulation results nstrate that the agents learn robust policies that reduce gy consumption while attaining the ultra-low delay requires of the advanced services.

    Original languageEnglish
    Title of host publication3rd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2021
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages344-346
    Number of pages3
    ISBN (Electronic)9781728176383
    DOIs
    Publication statusPublished - 2021 Apr 13
    Event3rd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2021 - Jeju Island, Korea, Republic of
    Duration: 2021 Apr 132021 Apr 16

    Publication series

    Name3rd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2021

    Conference

    Conference3rd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2021
    Country/TerritoryKorea, Republic of
    CityJeju Island
    Period21/4/1321/4/16

    Bibliographical note

    Publisher Copyright:
    © 2021 IEEE.

    Keywords

    • cell-free massive MIMO
    • distributive deep reinforcementing
    • joint communication omputing resource allocation
    • mobile edge network

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Networks and Communications
    • Computer Science Applications
    • Information Systems
    • Information Systems and Management

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