  The energy consumption of the fifth generation(5G) of mobile networks is one
of the major concerns of the telecom industry. However, there is not currently
an accurate and tractable approach to evaluate 5G base stations (BSs) power
consumption. In this article, we propose a novel model for a realistic
characterisation of the power consumption of 5G multi-carrier BSs, which builds
on a large data collection campaign. At first, we define a machine learning
architecture that allows modelling multiple 5G BS products. Then, we exploit
the knowledge gathered by this framework to derive a realistic and analytically
tractable power consumption model, which can help driving both theoretical
analyses as well as feature standardisation, development and optimisation
frameworks. Notably, we demonstrate that such model has high precision, and it
is able of capturing the benefits of energy saving mechanisms. We believe this
analytical model represents a fundamental tool for understanding 5G BSs power
consumption, and accurately optimising the network energy efficiency.
