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DRL-based Resource Management for Task-Centered Semantic Communication

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00381942" target="_blank" >RIV/68407700:21230/24:00381942 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/PIMRC59610.2024.10817269" target="_blank" >https://doi.org/10.1109/PIMRC59610.2024.10817269</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/PIMRC59610.2024.10817269" target="_blank" >10.1109/PIMRC59610.2024.10817269</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    DRL-based Resource Management for Task-Centered Semantic Communication

  • Original language description

    The evolution of Artificial Intelligence (AI) integrated with the Sixth-generation (6G) framework poses significant challenges to low-latency applications. Recently, semantic communication has emerged as a promising technique for future intelligent applications. However, the resource management problem combined with semantics is not fully explored. In this paper, we present a deep reinforcement learning-based twin-delayed deep deterministic policy gradient (TD3) for task-centered semantic communication. The proposed TD3 algorithm optimizes bandwidth, and semantic information and prioritizes data with maximum signal-to-noise ratio (SNR) for the efficient transmission of useful information. Simulation results demonstrate the effectiveness of the proposed TD3 scheme compared to state-of-the-art work in terms of transmission efficiency by up to 36% for varying users and up to 33% for varying SNR.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20202 - Communication engineering and systems

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2024 IEEE 35th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

  • ISBN

    9798350362244

  • ISSN

    2166-9570

  • e-ISSN

    2166-9589

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    IEEE

  • Place of publication

    Anchorage, Alaska

  • Event location

    Valencia

  • Event date

    Sep 2, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001450175000112