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Off-policy Learning for Remote Electrical Tilt Optimization
[article]
2020
arXiv
pre-print
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 orientation of the vertical tilt angle of the antenna to optimize Key Performance Indicators (KPIs) representing the Quality of Service (QoS) perceived by the users in cellular networks. Learning an improved tilt update policy is hard. On the one hand, coming up with a new policy in an online manner in a real network
arXiv:2005.10577v1
fatcat:7na2gn6cjnb7pe4fgaipleqegy