Huawei: iFaultCare - hidden trouble - AI Use Case Library - GSMA
Saturday March 1, 2025

Huawei: iFaultCare – hidden trouble

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Along with the development of wireless networks, new application scenarios pose higher requirements for network stability. However, the current fault operations and maintenance (O&M) mode can only passively wait for faults to occur and cannot prevent them in advance. For those faults of cell out-of-service, the network performance is severely affected before the fault is rectified, which would impact the reputation and business interests of operators.

Solution:

Indonesia XL and Huawei jointly applied iFaultCare in the fault management field to build fault management capabilities for pre-event prediction and prevention. According to the survey, fronthaul optical path faults and high temperature faults are important causes of cell out-of-service. iFaultCare uses machine learning technology to learn and model the signal characteristics of optical fibers and temperature control systems under different health conditions. In this way, optical fiber and temperature faults can be predicted 30 days and 7 days in advance, respectively. In addition, to maximize O&M efficiency, different work order priorities are set for identified potential faults based on the fault occurrence possibility and impact on the network.

Impact:

In the network of more than 10,000 sites in the XL West region of Indonesia, the cell out-of-service duration caused by faults is reduced by 24,315 to 88,968 hours per year, significantly improving the robustness of wireless network services.

Topic:  Operations and maintenance

Cost: Low

Location: Asia Pacific

MNOs and supporting organisations: Indonesia XL and Huawei