TY - GEN
T1 - IRS-Assisted Lossy Communications Under Correlated Rayleigh Fading
T2 - 2024 IEEE Global Communications Conference, GLOBECOM 2024
AU - Li, Guanchang
AU - Lin, Wensheng
AU - Li, Lixin
AU - He, Yixuan
AU - Yang, Fucheng
AU - Han, Zhu
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper focuses on an intelligent reflecting surface (IRS)-assisted lossy communication system with correlated Rayleigh fading. We analyze the correlated channel model and derive the outage probability of the system. Then, we design a deep reinforce learning (DRL) method to optimize the phase shift of IRS, in order to maximize the received signal power. Moreover, this paper presents results of the simulations conducted to evaluate the performance of the DRL-based method. The simulation results indicate that the outage probability of the considered system increases significantly with more correlated channel coefficients. Moreover, the performance gap between DRL and theoretical limit increases with higher transmit power and/or larger distortion requirement.
AB - This paper focuses on an intelligent reflecting surface (IRS)-assisted lossy communication system with correlated Rayleigh fading. We analyze the correlated channel model and derive the outage probability of the system. Then, we design a deep reinforce learning (DRL) method to optimize the phase shift of IRS, in order to maximize the received signal power. Moreover, this paper presents results of the simulations conducted to evaluate the performance of the DRL-based method. The simulation results indicate that the outage probability of the considered system increases significantly with more correlated channel coefficients. Moreover, the performance gap between DRL and theoretical limit increases with higher transmit power and/or larger distortion requirement.
KW - correlated Rayleigh channel
KW - deep reinforce learning
KW - intelligent reflecting surface
KW - lossy communications
KW - outage probability
UR - http://www.scopus.com/inward/record.url?scp=105000820298&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM52923.2024.10901564
DO - 10.1109/GLOBECOM52923.2024.10901564
M3 - 会议稿件
AN - SCOPUS:105000820298
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 3745
EP - 3750
BT - GLOBECOM 2024 - 2024 IEEE Global Communications Conference
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 December 2024 through 12 December 2024
ER -