Jul 11, 2024 · This paper investigates artificial intelligence (AI) empowered schemes for reconfigurable intelligent surface (RIS) assisted networks from the perspective of fast implementation. We formulate a weighted sum-rate maximization problem for a …

Apr 18, 2024 · Abstract: This paper investigates artificial intelligence (AI) empowered schemes for reconfigurable intelligent surface (RIS) assisted networks from the perspective of fast implementation. We formulate a weighted sum-rate maximization problem for a …

Apr 15, 2024 · With the rapid advancement of reconfigurable intelligence surfaces (RISs), a new approach with on-the-air diffractional deep neural networks $(\mathrm{D}^{2}\text{NN})$ can be utilized to enable semantic communications in the wave domain. This article proposes a new paradigm of RIS-based on-the-air semantic communications, where the ...

This paper explores the road to implementing the combination of RIS and AI, more specifically, integrating AI-enabled technologies into RIS-based frameworks for maximizing the practicality of RIS to facilitate the realization of smart radio propagation environments, elaborated from shallow to deep insights.

The synergy between RISs and MIMO systems, as well as advanced radio communications, highlights the importance of AI and ML in optimizing RIS-based beamforming. These technologies work together to solve pressing scientific and engineering challenges while promoting sustainability in NTN operations.

Abstract—This paper investigates artificial intelligence (AI) empowered schemes for reconfigurable intelligent surface (RIS) assisted networks from the perspective of fast implementation. We formulate a weighted sum-rate maximization problem for a …

Aug 12, 2024 · We explore how AI enhances RIS functionality in wireless networks, optimizing key aspects such as channel estimation (CE), rate maximization, expanding coverage, energy efficiency (EE), and...

A reconfigurable intelligent surface (RIS)-assisted multi-user downlink communication system over fading channels is investigated, where both non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes are employed.

This paper provides a review of the current optimization methods and artificial-intelligence-based methods for handling the constraints imposed by RISs and compares them in terms of the solution quality and computational complexity.

Fortunately, the impressive success of Artificial Intelligence (AI) in various fields has inspired its application in RIS-aided communications to address these challenges. In this paper, two pairs of dominant methodologies of using AI for RIS-aided wireless communications are discussed.