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Machine learning for non-orthogonal multiple access

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F24%3A50021617" target="_blank" >RIV/62690094:18450/24:50021617 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1201/9781003303114-6" target="_blank" >http://dx.doi.org/10.1201/9781003303114-6</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1201/9781003303114-6" target="_blank" >10.1201/9781003303114-6</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Machine learning for non-orthogonal multiple access

  • Original language description

    To achieve the diverse requirements for massive connectivity, low latency, high throughput, high reliability, and better fairness beyond fifth-generation (B5G), wireless networks must employ nonorthogonal multiple access (NOMA), a key enabling technology. The primary principle of NOMA is to accommodate multiple users within a shared resource block. Numerous B5G multiple access systems proposed in recent times can be considered specific implementations of the NOMA principle, which serves as a universal framework for such systems. This chapter summarizes the latest innovations, research findings, and applications in NOMA. It delves into the papers included in this special issue and examines their contributions in the context of existing research. Additionally, it highlights the upcoming research challenges associated with NOMA in the context of B5G and future generations.

  • Czech name

  • Czech description

Classification

  • Type

    C - Chapter in a specialist book

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

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

  • Book/collection name

    Intelligent Communication Networks: Research and Applications

  • ISBN

    978-1-00-330311-4

  • Number of pages of the result

    19

  • Pages from-to

    135-153

  • Number of pages of the book

    256

  • Publisher name

    CRC Press

  • Place of publication

    Florida

  • UT code for WoS chapter