Huawei ICNMaster Vastly Improves O&M ProcessesHuawei ICNMaster Vastly Improves O&M Processes

The rapid adoption of cloud-native technology, multi-RAT deployments, and regional networks has led to increased network complexity and significant O&M challenges in the telecommunications industry.

Accelerating digital transformation with AI-based technological innovation has become a transformation trend in the communications industry. In this context, how to use new technologies to improve core network O&M experience and O&M process efficiency becomes an urgent issue to be addressed.

To alleviate this issue, ICNMaster, the core network area application of Huawei Telecom Foundation Model provides provide a unified portal for intelligent interaction and capability scheduling. It introduces model training of massive professional domain knowledge and core network data to enhance intelligent analysis capabilities, and integrates intelligence to reshape the O&M process. As a result, operators consistently gain optimal O&M experiences through a highly autonomous core network.

Overcoming core network O&M challenges

Operators face a number of critical core network issues and a significant percentage (42%) experienced global core network incidents with 50% of users negatively effected by incidents. As core networks become more complex, the lack of experienced domain experts, inefficient cross-departmental collaborations, and manual operations relying on discrete tools all result in low O&M efficiency. Integrating automation and intelligence into the network O&M lifecycle can greatly improve network O&M processing capabilities, significantly shorten the O&M processing time, and improve overall efficiency.

Huawei ICNMaster Solution (core network area application of Huawei Telecom Foundation Model)

The Huawei ICNMaster Solution has taken the lead in putting the core operation and maintenance large model into production, bringing great improvement in efficiency and quality. By offering intelligent replacement of some manual activities, ICNMaster introduces a new paradigm for achieving network growth without increasing the workforce.

This solution not only provides a unified cloud-network visualization front-end, signaling storm prevention and control before and after networks operations, and optimal flow control parameter recommendations, but also provides an AI-based digital assistant and digital expert solution which reshapes the O&M experience by enabling core network O&M teams to perform maintenance tasks through natural language Q&A dialogs.

Through automatic orchestration of intelligent bodies, the ICNMaster solution provides automatic complaint classification, fast fault awareness and automatic alarm analysis. The solution effectively converts network O&M from manual approaches that rely on discrete tools to intelligence-driven interventions. The value of ICNMaster rests in its high reliability, user-friendly experience, and sustained high efficiency.

China Mobile and Huawei: Self-intelligent network O&M infrastructure

In line with China Mobile's goal of building a high-level autonomous core network with fast delivery, optimal quality, high resource efficiency, low O&M costs, and simplified operations, Zhejiang Mobile and Huawei have partnered to provide these digital assistance and expertise for core network O&M based on the foundation model.

ICNMaster's complaint handling experts significantly boost complaint handling and increases precision to 87% while also employing signaling analysis to identify root causes of network interruptions.

In complaint handling scenarios, operators employ the complaint handling agent to quickly understand intention, demarcate complex processes, and simplify the operation process. For Zhejiang Mobile, the Huawei ICNMaster solution accelerates the closure of the entire complaint handling process, with over 75% of complaint work orders now handled through a much shorter and simpler procedure. Moreover, the end-to-end handling time for complaint work orders is reduced from 14.6 hours to 5.2 hours, improving efficiency by 64%.

In monitoring and troubleshooting scenarios, personnel can employ the one-click alarm handling agent to access precise alarm knowledge through real-time Q&A dialogs and acquire case recommendation and intelligent diagnosis. As a result, the average Core Network alarm handling duration is reduced from 1.5 hours to 0.2 hours, improving efficiency by 87%. ICNMaster is currently in trial operation in Qinghai and Guangdong, besides Zhejiang Mobile.

Conclusion

In terms of core network O&M processes, industry customers have strict requirements regarding service SLAs which can pose significant challenges. The partnership between operators and Huawei is designed to meet the goal of building autonomous networks with optimal quality, low O&M costs, and high resource efficiency. Huawei will continue launching more intelligent solutions with the goal to deliver high-performance core networks that will drive the rapid development of digital economy.