A self-regulating power-control scheme using reinforcement learning for d2d communication networks

HIGHLIGHTS

• who: Tae-Won Ban from the Department of Intelligent Engineering, Gyeongsang National University have published the Article: A Self-Regulating Power-Control Scheme Using Reinforcement Learning for D2D Communication Networks, in the Journal: Sensors 2022, 22, 4894. of /2022/
• what: The authors investigate a power control problem for overlay device-to-device (D2D) networks relying on a deep deterministic policy gradient (DDPG) which is a model-free off-policy algorithm for learning continuous actions such as transmitting power levels. The authors propose a DDPG-based self-regulating power control scheme whereby each D2D transmitter can . . .
  

   

  

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