TY - GEN
T1 - Adaptive Passive Beamforming in RIS-Aided Communications with Q-Learning
AU - Chene, Thomas
AU - Bounhar, Oumaima
AU - Othman, Ghaya Rekaya Ben
AU - Damen, Oussama
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - Reconfigurable Intelligent Surfaces (RIS) appear as a promising solution to combat wireless channel fading and interferences. However, the elements of the RIS need to be properly oriented to boost the data transmission rate. In this work, we propose a new strategy to adaptively configure the RIS without Channel State Information (CSI). Our goal is to minimize the number of RIS configurations to be tested to find the optimal one. We formulate the problem as a stochastic shortest path problem, and use Q-Learning to solve it.
AB - Reconfigurable Intelligent Surfaces (RIS) appear as a promising solution to combat wireless channel fading and interferences. However, the elements of the RIS need to be properly oriented to boost the data transmission rate. In this work, we propose a new strategy to adaptively configure the RIS without Channel State Information (CSI). Our goal is to minimize the number of RIS configurations to be tested to find the optimal one. We formulate the problem as a stochastic shortest path problem, and use Q-Learning to solve it.
KW - Bayesian Inference
KW - Q Learning
KW - Reconfigurable Intelligent Surfaces (RIS)
UR - https://www.scopus.com/pages/publications/105006408735
U2 - 10.1109/WCNC61545.2025.10978715
DO - 10.1109/WCNC61545.2025.10978715
M3 - Conference contribution
AN - SCOPUS:105006408735
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2025 IEEE Wireless Communications and Networking Conference, WCNC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 IEEE Wireless Communications and Networking Conference, WCNC 2025
Y2 - 24 March 2025 through 27 March 2025
ER -