RIS-Codes-Collection: A Complete Collection contains the Codes for RIS(IRS) Researches.

Joint Transmit Beamforming and Phase Shifts Design with Deep Reinforcement Learning

IEEE WCNC 2023: Deep Reinforcement Learning for Secrecy Energy-Efficient UAV Communication with Reconfigurable Intelligent Surfaces

Joint Transmit Beamforming and Phase Shifts Design with Deep Reinforcement Learning Under the Phase-Dependent Amplitude Model

Simulation Codes for "Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach"

This is the code implementation for the GMML algorithm.

Multi-RIS-aided Wireless Systems: Statistical Characterization and Performance Analysis, IEEE Transactions on Communications, Sep. 2021.

Aerial Reconfigurable Intelligent Surface-Aided Wireless Communication Systems, IEEE PIMRC, 2021

OpenRIS is an open-source reconfigurable intelligent surface (RIS) project

Simulation code for "On the Secrecy Rate under Statistical QoS Provisioning for RIS-assisted MISO Wiretap Channel," by V. Kumar, M. F. Flanagan, D. W. Kwan Ng, and L. -N. Tran, IEEE Global Communications Conference (GLOBECOM), 2021, pp. 1-6, doi: 10.1109/GLOBECOM46510.2021.9685957.

This repository is accompanying the papers "Artificial Fast Fading from Reconfigurable Surfaces Enables Ultra-Reliable Communications" (SPAWC 2021), "RIS-Assisted Statistical Channel Shaping for Ultra-High Reliability" (WSA 2021), and "Reconfigurable Intelligent Surface Phase Hopping for Ultra-Reliable Communications" (TWC, DOI:10.1109/TWC.2022.…

Matlab code for "A novel channel model for reconfigurable intelligent surfaces with consideration of polarization and switch impairments"

Closed-Form Global Optimization of Beyond Diagonal Reconfigurable Intelligent Surfaces

Worst-case MSE Minimization for RIS-assisted mmWave MU-MISO Systems with Hardware Impairments and CSI Imperfection

Implementation of the performance evaluation of "On the Impact of Control Signaling in RIS-Empowered Wireless Communications"

Optimization of Transmit Beamforming based on Unsupervised Learning With Channel Covariances for MISO Downlink Assisted by Reconfigurable Intelligent Surfaces

Pareto Frontier for the Performance-Complexity Trade-Off in Beyond Diagonal Reconfigurable Intelligent Surfaces

Beyond Diagonal Reconfigurable Intelligent Surfaces Utilizing Graph Theory: Modeling, Architecture Design, and Optimization

Codes for reproducing the numerical results reported in: "An Orchestration Framework for Open System Models of Reconfigurable Intelligent Surfaces" by V. Croisfelt, F. Devoti, F. Saggese, V. Sciancalepore, X. Costa-Pérez, and P. Popovski.

Federated Learning and 6G Project