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Found 6 papers, 2 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.
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.
Simulation of machine learning-based 6G systems in virtual worlds
Digital representations of the real world are being used in many applications, such as augmented reality.
Generating MIMO Channels For 6G Virtual Worlds Using Ray-tracing Simulations
Some 6G use cases include augmented reality and high-fidelity holograms, with this information flowing through 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.
