Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks

@article{Nasir2019MultiAgentDR,
  title={Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks},
  author={Yasar Sinan Nasir and D. Guo},
  journal={IEEE Journal on Selected Areas in Communications},
  year={2019},
  volume={37},
  pages={2239-2250}
}
  • Yasar Sinan Nasir, D. Guo
  • Published 2019
  • Computer Science, Engineering, Mathematics
  • IEEE Journal on Selected Areas in Communications
This work demonstrates the potential of deep reinforcement learning techniques for transmit power control in wireless networks. [...] Key Method Both random variations and delays in the CSI are inherently addressed using deep ${Q}$ -learning. For a typical network architecture, the proposed algorithm is shown to achieve near-optimal power allocation in real time based on delayed CSI measurements available to the agents. The proposed scheme is especially suitable for practical scenarios where the system model is…Expand
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