Related papers: Multi-agent Reinforcement Learning-based Joint Pre…

This work considers a reconfigurable intelligent surface (RIS)-aided cell-free massive multiple-input multiple-output (MIMO) system with RIS spatial correlation and electromagnetic interference (EMI). We propose a two-phase channel…

Active reconfigurable intelligent surface (RIS) has attracted significant attention as a recently proposed RIS architecture. Owing to its capability to amplify the incident signals, active RIS can mitigate the multiplicative fading effect…

Federated learning (FL), as a disruptive machine learning paradigm, enables the collaborative training of a global model over decentralized local datasets without sharing them. It spans a wide scope of applications from Internet-of-Things…

In practical cell-free (CF) massive multiple-input multiple-output (MIMO) networks with distributed and low-cost access points, the asynchronous arrival of signals at the user equipments increases multi-user interference that degrades the…

Reconfigurable intelligent surface (RIS) has been anticipated to be a novel cost-effective technology to improve the performance of future wireless systems. In this paper, we investigate a practical RIS-aided multiple-input-multiple-output…

Reconfigurable intelligent surfaces (RIS) have emerged as a promising technology for enhancing wireless communication by dynamically controlling signal propagation in the environment. However, their efficient deployment relies on accurate…

Reconfigurable Intelligent Surfaces (RIS) are pivotal for next-generation smart radio environments, yet their practical deployment is severely bottlenecked by the intractable computational overhead of Channel State Information (CSI)…

Multi-Agent Systems (MAS) excel at accomplishing complex objectives through the collaborative efforts of individual agents. Among the methodologies employed in MAS, Multi-Agent Reinforcement Learning (MARL) stands out as one of the most…

Reconfigurable Intelligent Surfaces (RIS) are passive or semi-passive heterogeneous metasurfaces and consist of many tunable elements. RIS is gaining momentum as a promising new technology to enable transforming the propagation environment…

This paper presents a scalable beamforming design for maximizing the spectral efficiency (SE) of multi-reconfigurable intelligent surface (RIS)-aided communications through joint optimization of the precoder and RIS phase shifts in…

Transmissive reconfigurable intelligent surfaces (RIS) represent a transformative architecture for future wireless networks, enabling a paradigm shift from traditional costly base stations to low-cost, energy-efficient transmitters. This…

This paper proposes a novel phase shift design for cell-free massive multiple-input and multiple-output (MIMO) systems assisted by reconfigurable intelligent surface (RIS), which only utilizes channel statistics to achieve the uplink sum…

Reconfigurable intelligent surfaces (RISs) are envisioned to be a disruptive wireless communication technique that is capable of reconfiguring the wireless propagation environment. In this paper, we study a free-space RIS-assisted…

Reconfigurable intelligent surface (RIS) is a promising technology that can reshape the electromagnetic environment in wireless networks, offering various possibilities for enhancing wireless channels. Motivated by this, we investigate the…

Efficient computation offloading in multi-UAV edge networks becomes particularly challenging in dense urban areas, where line-of-sight (LoS) links are frequently blocked and user demand varies rapidly. Reconfigurable intelligent surfaces…

Multi-Agent Reinforcement Learning (MARL) has become a classic paradigm to solve diverse, intelligent control tasks like autonomous driving in Internet of Vehicles (IoV). However, the widely assumed existence of a central node to implement…

Large intelligent surface (LIS) has recently emerged as a potential low-cost solution to reshape the wireless propagation environment for improving the spectral efficiency. In this paper, we consider a downlink millimeter-wave (mmWave)…

Information theoretic sensor management approaches are an ideal solution to state estimation problems when considering the optimal control of multi-agent systems, however they are too computationally intensive for large state spaces,…

Continuous efforts have been devoted to integrate millimeter wave (mmWave) and terahertz (THz) bands into future communication standards in order to overcome the bandwidth shortage problem and achieve high data rates, primarily through…

It is a challenging problem to jointly optimize the base station (BS) precoding matrix and the reconfigurable intelligent surface (RIS) phases simultaneously in a RIS-assisted multiple-user multiple-input-multiple-output (MU-MIMO) scenario…