• DOI:10.1109/JSAC.2019.2933973
Corpus ID: 58007060

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

View on IEEE

arxiv.org

Save to Library

Create Alert

Cite

Launch Research Feed