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Found 4 papers, 0 papers with code
Cell-Free Data Power Control Via Scalable Multi-Objective Bayesian Optimisation
Cell-free multi-user multiple input multiple output networks are a promising alternative to classical cellular architectures, since they have the potential to provide uniform service quality and high resource utilisation over the entire coverage area of the network.
Reinforcement Learning for Efficient and Tuning-Free Link Adaptation
In this context, we propose a latent learning model for link adaptation that exploits the correlation between data transmission parameters.
When Machine Learning Meets Wireless Cellular Networks: Deployment, Challenges, and Applications
Artificial intelligence (AI) powered wireless networks promise to revolutionize the conventional operation and structure of current networks from network design to infrastructure management, cost reduction, and user performance improvement.
Constrained Thompson Sampling for Wireless Link Optimization
We model rate selection as a stochastic multi-armed bandit (MAB) problem, where a finite set of transmission rates are modeled as independent bandit arms.
