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

作　　者：Qin Cai Wang Chaowei Wang Weidong Zhang Yinghai 

机构地区：[1]School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876 , China [2]Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunication , Beijing 100876 , China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2019年第3期35-43,80,共10页中国邮电高校学报（英文版）

基　　金：supported by the National Key R&D Program of China (2017YFC0804404);the Beijing Talents Foundation (2017000020124G067)

摘　　要：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(DPC) approach 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.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(DPC) approach 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.

关 键 词：power control DEEP REINFORCEMENT learning RELAY DOWNLINK 

分 类 号：TN[电子电信]