TY - GEN
T1 - Reflection Coefficients Optimization in IRS-assisted Communication
T2 - 13th International Conference on Wireless Communications and Signal Processing, WCSP 2021
AU - Hu, Haixin
AU - Li, Lixin
AU - Lin, Wensheng
AU - Li, Xu
AU - Hant, Zhu
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Intelligent reflecting surface (IRS) alters the signal propagation via tuning a large number of passive reflection units, and is a promising solution to enhance the wireless communication. In this paper, we aim to improve the level of mutual information of the IRS-assisted communication system by optimizing the IRS reflection coefficients. Specifically, in order to solve the established IRS reflection coefficients optimization problem, the dynamic adjustment process is first modeled as an evolutionary game (EG) model, and then the replication dynamic equations about the revenue function are established. Next, for the single-mode constraints of the reflection coefficients, the reinforcement learning (RL) method is adopted, and the strategy iteration algorithm is used to solve the evolutionary stability strategy. Simulation results demonstrate that our proposed algorithm achieves substantially increased mutual information compared to the traditional scheme without IRS and another benchmark scheme.
AB - Intelligent reflecting surface (IRS) alters the signal propagation via tuning a large number of passive reflection units, and is a promising solution to enhance the wireless communication. In this paper, we aim to improve the level of mutual information of the IRS-assisted communication system by optimizing the IRS reflection coefficients. Specifically, in order to solve the established IRS reflection coefficients optimization problem, the dynamic adjustment process is first modeled as an evolutionary game (EG) model, and then the replication dynamic equations about the revenue function are established. Next, for the single-mode constraints of the reflection coefficients, the reinforcement learning (RL) method is adopted, and the strategy iteration algorithm is used to solve the evolutionary stability strategy. Simulation results demonstrate that our proposed algorithm achieves substantially increased mutual information compared to the traditional scheme without IRS and another benchmark scheme.
KW - evolutionary game (EG)
KW - Intelligent reflecting surface (IRS)
KW - reinforcement learning (RL)
KW - strategy iteration algorithm
UR - http://www.scopus.com/inward/record.url?scp=85123354515&partnerID=8YFLogxK
U2 - 10.1109/WCSP52459.2021.9613652
DO - 10.1109/WCSP52459.2021.9613652
M3 - 会议稿件
AN - SCOPUS:85123354515
T3 - 13th International Conference on Wireless Communications and Signal Processing, WCSP 2021
BT - 13th International Conference on Wireless Communications and Signal Processing, WCSP 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 20 October 2021 through 22 October 2021
ER -