Deep-Learning-Aided Detection for Reconfigurable Intelligent Surfaces

Understand

This paper presents a deep learning (DL) approach for estimating and detecting symbols in signals transmitted through reconfigurable intelligent surfaces (RIS).

• The proposed network utilizes fully connected layers to estimate channels and phase angles from a reflected signal received through an RIS.
• Because the proposed network can estimate and detect symbols without any pilot signaling, this method reduces the overhead required for transmission.
• The improvements achieved by this method are quantified in terms of the bit-error rate, outperforming traditional detectors.