Sionna: An Open-Source Library for Next-Generation Physical Layer Research

This advanced and complex project implements an AI-powered optimization system for 5G Open RAN networks. Using machine learning and deep learning, the system optimizes network performance by detecting anomalies, predicting network traffic, and dynamically allocating resources.

M. Polese, F. Restuccia, and T. Melodia, "DeepBeam: Deep Waveform Learning for Coordination-Free Beam Management in mmWave Networks", Proc. of ACM Intl. Symp. on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc), July 2021.

Camera based beam prediction

This package analyzes the age of information (AoI) in a wireless network, providing metrics for network performance evaluation. It can be easily integrated into simulation environments for research on AoI.

Code containing RRM simulation using RL in a scenario with RAN slicing.

Learning Environment-aware and hardware-compatible beam-forming codebooks

Comyx is an optimized and modular Python library for simulating wireless communication systems

Vision-Aided Beam Tracking

RAN Fusion a NextG RAN Simulator

In this repository, you will find the source code for analyzing tracks during data transmission using Software Defined Radios. Metrics about error positioning and error syndrome are attached.

RAN Simulator for OAICT

Combination of federated learning algorithm and 6G technology.

THz visibility prediction and AP assignment simulator