TY - GEN
T1 - GNN-Based Data Rate Maximization in Double Intelligent Reflecting Surface (IRS)-Aided Communication System
AU - Li, Kaixin
AU - Peng, Limei
AU - Ho, Pin Han
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper explores the utilization of double intelligent reflecting surfaces (IRSs) in wireless communication systems to enhance signal propagation. By dynamically adjusting the reflecting elements of the IRSs, we can efficiently manipulate the signal direction to improve the communication performance such as data rate. Nonetheless, due to the passive nature of the reflecting elements, it is quite challenging to accurately measure the channels directly between the base station (BS), the IRS, and the users based on the conventional channel estimation methods. To address this, we propose to apply a machine learning algorithm that bypasses the traditional channel estimation process and optimizes system parameters by directly extracting information from the received pilot signal. Through extensive simulations, we demonstrate the effectiveness of our proposed method in enhancing the performance of wireless systems incorporating double IRSs.
AB - This paper explores the utilization of double intelligent reflecting surfaces (IRSs) in wireless communication systems to enhance signal propagation. By dynamically adjusting the reflecting elements of the IRSs, we can efficiently manipulate the signal direction to improve the communication performance such as data rate. Nonetheless, due to the passive nature of the reflecting elements, it is quite challenging to accurately measure the channels directly between the base station (BS), the IRS, and the users based on the conventional channel estimation methods. To address this, we propose to apply a machine learning algorithm that bypasses the traditional channel estimation process and optimizes system parameters by directly extracting information from the received pilot signal. Through extensive simulations, we demonstrate the effectiveness of our proposed method in enhancing the performance of wireless systems incorporating double IRSs.
KW - graph neural network (GNN)
KW - Intelligent reflecting surface (IRS)
KW - reconfig-urable intelligent surfaces (RIS)
UR - http://www.scopus.com/inward/record.url?scp=85176723959&partnerID=8YFLogxK
U2 - 10.1109/NaNA60121.2023.00080
DO - 10.1109/NaNA60121.2023.00080
M3 - Conference contribution
AN - SCOPUS:85176723959
T3 - Proceedings - 2023 International Conference on Networking and Network Applications, NaNA 2023
SP - 447
EP - 452
BT - Proceedings - 2023 International Conference on Networking and Network Applications, NaNA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on Networking and Network Applications, NaNA 2023
Y2 - 18 August 2023 through 21 August 2023
ER -