Dynamic and efficient resource allocation for 5G end‐to‐end network slicing: A multi‐agent deep reinforcement learning approach

Ähnliche Einträge

• Optimization of resource allocation in 5G networks: A network slicing approach with hybrid NOMA for enhanced uRLLC and eMBB coexistence
  von: Rebba Chandra Sekhar, et al.
  Veröffentlicht: (2024)
• Transit Archimedes optimization algorithm enabled deep learning for power and resource allocation NOMA technique for 5G cellular systems
  von: Prasheel Thakre, et al.
  Veröffentlicht: (2024)
• RETRACTED: Efficient machine learning‐based hybrid resource allocation for device‐to‐device underlay communication in 5G wireless networks
  von: Malle Gopal, et al.
  Veröffentlicht: (2024)
• Slice admission control in 5G cloud radio access network using deep reinforcement learning: A survey
  von: Mohsen Khani, et al.
  Veröffentlicht: (2024)
• Power allocation for enhancing energy efficiency in unmanned aerial vehicle networks
  von: J. T. Anita Rose, et al.
  Veröffentlicht: (2024)