DQN-Based Adaptive Modulation Scheme Over Wireless Communication Channels

  • Lee, Donggu; 
  • Sun, Young Ghyu; 
  • Kim, Soo Hyun; 
  • Sim, Isaac; 
  • Hwang, Yu Min; 
  • ... Shin, Yoan; 
  • 외 2명
Citations

WEB OF SCIENCE

33
Citations

SCOPUS

41

초록

In this letter, to improve data rate over wireless communication channels, we propose a deep Q network (DQN)-based adaptive modulation scheme by using Markov decision process (MDP) model. The proposed algorithm makes the reinforcement learning agent to select rate region boundaries as the states, which divide signal-to-noise ratio (SNR) range into rate regions. The simulation results show that spectral efficiency can be improved on the average by 0.5395 bps/Hz in wide SNR range.

키워드

Modulation; Signal to noise ratio; Learning (artificial intelligence); Adaptation models; Wireless communication; Adaptive systems; Neural networks; Adaptive modulation; deep learning; deep Q network; reinforcement learning
제목
DQN-Based Adaptive Modulation Scheme Over Wireless Communication Channels
저자
Lee, Donggu; Sun, Young Ghyu; Kim, Soo Hyun; Sim, Isaac; Hwang, Yu Min; Shin, Yoan; Kim, Dong In; Kim, Jin Young
DOI
10.1109/LCOMM.2020.2978390
발행일
2020-06
유형
Article
저널명
IEEE Communications Letters
권
24
호
6
페이지
1289 ~ 1293