Q-learning based power control algorithm for D2D communication

@article{Nie2016QlearningBP,
  title={Q-learning based power control algorithm for D2D communication},
  author={Shiwen Nie and Zhiqiang Fan and Ming Zhao and Xinyu Gu and Lin Zhang},
  journal={2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)},
  year={2016},
  pages={1-6}
}
In this paper, reinforcement learning (RL) based power control algorithm in underlay D2D communication is studied. The approach we use regards D2D communication as a multi-agents system, and power control is achieved by maximizing system capacity while maintaining the requirement of quality of service(QoS) from cellular users. We propose two RL based power control methods for D2D users, i.e., team-Q learning and distributed-Q learning. The former is a centralized method in which only one Q… CONTINUE READING
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