Adaptive Passive Beamforming in RIS-Aided Communications With Q-Learning
By: Thomas Chêne , Oumaïma Bounhar , Ghaya Rekaya-Ben Othman and more
Potential Business Impact:
Makes wireless signals stronger without needing to know everything.
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.
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