Power Supply Fault Prediction
OwnerLackis Eleftheriadis, Agustin Valencia +1inventors
InventorsLackis Eleftheriadis, Agustin Valencia, Oleg Gorbatov
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Abstract
Disclosed are apparatuses and methods for power supply fault prediction for a Radio Base Station (RBS) forming part of a communication network. The method comprises obtaining measurements of at least one of: input power characteristics of a Powers Supply Unit (PSU) of the RBS: power output characteristics of a power distribution unit of the RBS; and power input characteristics of radio units of the RBS. The method further comprises converting the obtained measurements into performance metrics characterising the performance of a RBS power supply. The method also comprises processing the performance metrics using a Machine Learning (ML) model to generate a power supply fault prediction.
Claims21
1-33. (canceled)
A computer-implemented method for power supply fault prediction for a Radio Base Station (RBS) forming part of a communication network, the method comprising:
- obtaining measurements of at least one of:
- input power characteristics of a Power Supply Unit (PSU) of the RBS, power output characteristics of a power distribution unit (PDU) of the RBS, and power input characteristics of radio units (RU) of the RBS;
- converting the obtained measurements into performance metrics characterising the performance of a RBS power supply;
- and
- processing the performance metrics using a Machine Learning (ML) model to generate a power supply fault prediction.
A Radio Base Station (RBS) comprising processing circuitry and a memory containing instructions executable by the processing circuitry, whereby the RBS is operable to:
- obtain measurements of at least one of:
- input power characteristics of a Power Supply Unit (PSU) of the RBS, power output characteristics of a power distribution unit (PDU) of the RBS, and power input characteristics of radio units (RU) of the RBS;
- convert the obtained measurements into performance metrics characterising the performance of a RBS power supply;
- and
- process the performance metrics using a Machine Learning (ML) model to generate power supply fault predictions.
Dependencies are inferred from the claim text.