%0 Journal Article
%A 秦彩 王朝炜 王卫东 张英海
%T Dynamic power control for relay-aided transmission based on deep reinforcement learning
%D 2019
%R 10.19682/j.cnki.1005-8885.2019.0016
%J 中国邮电高校学报（英文）
%P 35-43
%V 26
%N 3
%X 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.
%U https://jcupt.bupt.edu.cn/CN/10.19682/j.cnki.1005-8885.2019.0016