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20202026
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cs.LG2022

Learning Optimal Antenna Tilt Control Policies: A Contextual Linear Bandit Approach

Filippo Vannella, Alexandre Proutiere, Yassir Jedra +1

Controlling antenna tilts in cellular networks is imperative to reach an efficient trade-off between network coverage and capacity. In this paper, we devise algorithms learning opt…

cs.LG2021

A Graph Attention Learning Approach to Antenna Tilt Optimization

Yifei Jin, Filippo Vannella, Maxime Bouton +2

6G will move mobile networks towards increasing levels of complexity. To deal with this complexity, optimization of network parameters is key to ensure high performance and timely…

cs.LG2020

A Safe Reinforcement Learning Architecture for Antenna Tilt Optimisation

Erik Aumayr, Saman Feghhi, Filippo Vannella +2

Safe interaction with the environment is one of the most challenging aspects of Reinforcement Learning (RL) when applied to real-world problems. This is particularly important when…

cs.LG2020

Remote Electrical Tilt Optimization via Safe Reinforcement Learning

Filippo Vannella, Grigorios Iakovidis, Ezeddin Al Hakim +2

Remote Electrical Tilt (RET) optimization is an efficient method for adjusting the vertical tilt angle of Base Stations (BSs) antennas in order to optimize Key Performance Indicato…

cs.LG2020

Off-policy Learning for Remote Electrical Tilt Optimization

Filippo Vannella, Jaeseong Jeong, Alexandre Proutiere

We address the problem of Remote Electrical Tilt (RET) optimization using off-policy Contextual Multi-Armed-Bandit (CMAB) techniques. The goal in RET optimization is to control the…