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Found 6 papers, 3 papers with code
CAVIAR: Co-simulation of 6G Communications, 3D Scenarios and AI for Digital Twins
Digital twins are an important technology for advancing mobile communications, specially in use cases that require simultaneously simulating the wireless channel, 3D scenes and machine learning.
Feedback-feedforward Signal Control with Exogenous Demand Estimation in Congested Urban Road Networks
To cope with varying and highly uncertain traffic patterns, a novel network-wide traffic signal control strategy based on the store-and-forward model of a traffic network is proposed.
Intent-aware Radio Resource Scheduling in a RAN Slicing Scenario using Reinforcement Learning
In this scenario, radio resource scheduling (RRS) is responsible for dealing with scarce and limited frequency spectrum resources available at the RAN domain while fulfilling the slice intents.
Distributed decentralized receding horizon control for very large-scale networks with application to satellite mega-constellations
A distributed and decentralized receding horizon control solution is put forward, which: i) takes communication delays into account; ii) allows local communication exclusively; and iii) whose computational and memory requirements in each computational unit do not scale with the dimension of the network.
5G MIMO Data for Machine Learning: Application to Beam-Selection using Deep Learning
The increasing complexity of configuring cellular networks suggests that machine learning (ML) can effectively improve 5G technologies.
