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Jean Baptiste Gros

Publications and source records attributed to Jean Baptiste Gros.

3 recordsLinked to original sources

Model-free Optimization and Experimental Validation of RIS-assisted Wireless Communications under Rich Multipath Fading

Reconfigurable intelligent surface (RIS) devices have emerged as an effective way to control the propagation channels for enhancing the end-users' performance. However, RIS optimization involves configuring the radio frequency response of a large number of radiating elements, which is challenging in real-world applications due to high computational complexity. In this paper, a model-free cross-entropy (CE) algorithm is proposed to optimize the binary RIS configuration for improving the signal-to-noise ratio (SNR) at the receiver. One key advantage of the proposed method is that it only requires system performance indicators, e.g., the received SNR, without the need for channel models or channel state information. Both simulations and experiments are conducted to evaluate the performance of the proposed CE algorithm. This study provides an experimental demonstration of the channel hardening effect in a multi-antenna RIS-assisted wireless system under rich multipath fading.

cs.IT↗

Reconfigurable Intelligent Surface-assisted Classification of Modulations using Deep Learning

The fifth generating (5G) of wireless networks will be more adaptive and heterogeneous. Reconfigurable intelligent surface technology enables the 5G to work on multistrand waveforms. However, in such a dynamic network, the identification of specific modulation types is of paramount importance. We present a RIS-assisted digital classification method based on artificial intelligence. We train a convolutional neural network to classify digital modulations. The proposed method operates and learns features directly on the received signal without feature extraction. The features learned by the convolutional neural network are presented and analyzed. Furthermore, the robust features of the received signals at a specific SNR range are studied. The accuracy of the proposed classification method is found to be remarkable, particularly for low levels of SNR.

eess.SP↗

Multi-path fading and interference mitigation with Reconfigurable Intelligent Surfaces

We exploit multi-path fading propagation to improve both the signal-to-interference-plus-noise-ratio and the stability of wireless communications within electromagnetic environments that support rich multipath propagation. Quasi-passive propagation control with multiple binary reconfigurable intelligent surfaces is adopted to control the stationary waves supported by a metallic cavity hosting a software-defined radio link. Results are demonstrated in terms of the error vector magnitude minimization of a quadrature phase-shift modulation scheme under no-line-of-sight conditions. It is found that the magnitude of fluctuation of received symbols is reduced to a stable constellation by increasing the number of individual surfaces, or elements, thus demonstrating channel hardening. By using a second software-defined radio device as a jammer, we demonstrate the ability of the RIS to mitigate the co-channel interference by channel hardening. Results are of particular interest in smart radio environments for mobile network architectures beyond 5G.

eess.SP↗