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Knowledge Defined Networking for 6G: A Reinforcement Learning Example for Resource Management

  • Tuǧçe Bilen*
  • , Mehmet Özdem
  • , Erol Koçoǧlu
  • *Bu çalışma için yazışmadan sorumlu yazar
  • Turk Telekom
  • Istanbul Technical University

Araştırma sonucu: Dergiye katkıKonferans makalesibilirkişi

1 Atıf (Scopus)

Özet

6G networks are expected to revolutionize connectivity, offering significant improvements in speed, capacity, and smart automation. However, existing network designs will struggle to handle the demands of 6G, which include much faster speeds, a huge increase in connected devices, lower energy consumption, extremely quick response times, and better mobile broadband. To solve this problem, incorporating the artificial intelligence (AI) technologies has been proposed. This idea led to the concept of Knowledge-Defined Networking (KDN). KDN promises many improvements, such as resource management, routing, scheduling, clustering, and mobility prediction. The main goal of this study is to optimize resource management using Reinforcement Learning.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)1455-1460
Sayfa sayısı6
DergiInternational Conference on Computer Science and Engineering, UBMK
Basın numarası2025
DOI'lar
Yayın durumuYayınlandı - 2025
Etkinlik10th International Conference on Computer Science and Engineering, UBMK 2025 - Istanbul, Türkiye
Süre: 17 Eyl 202521 Eyl 2025

Bibliyografik not

Publisher Copyright:
© 2025 IEEE.

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