The Journal of China Universities of Posts and Telecommunications ›› 2019, Vol. 26 ›› Issue (3): 35-43.doi: 10.19682/j.cnki.1005-8885.2019.0016

• Wireless • Previous Articles     Next Articles

Dynamic power control for relay-aided transmission based on deep reinforcement learning

  

  • Received:2019-01-25 Revised:2019-04-09 Online:2019-06-30 Published:2019-06-30
  • Supported by:
    National Key R&D Program of China

Abstract: Using relay in the wireless communication network is an efficient way to ensure the data transmission to the distant receiver. In this paper, a dynamic power control approach (DPC) is proposed for the amplify-and-forward (AF) relay-aided downlink transmission scenario based on deep reinforcement learning (DRL) to reduce the co-channel interference caused by spectrum sharing among different nodes. The relay works in a two-way half-duplex (HD) mode. Specifically, the power control of the relay is modeled as a Markov decision process (MDP) and the sum rate maximization of the network is formulated as a DRL problem. Simulation results indicate that the proposed method can significantly improve the system sum rate.

Key words: power control, deep reinforcement learning, relay, downlink