Autonomous Networks

China Mobile has built the world’s largest private 5G network for CATL, a battery supplier headquartered in Fujian, China. By developing AN service capabilities, rapid and agile end-to-end delivery of ultra large-scale 5G private networks has become a reality, with challenges like complex business cases and a broad coverage area for enterprises solved.

China Mobile Fujian focuses on six key delivery elements – organization, process, command, system, autonomy and guarantee – to empower digital transformation of CATL’s entire production process of high-end manufacturing, including:

• Agile activation – through rule decoupling and flexible configuration, cross-domain processes are correlated to realize one-click automatic activation of end-to-end services across different provinces and office parks/campuses.

• Self-service ability for business customers – two types of standardized 5G private network products (network ability and operation and maintenance service) have been launched to provide “atomized” service capabilities for business customers (where computing environments are geographically dispersed across multicloud, hybrid cloud and on-premises infrastructure) and to support rapid commercialization of products.

• Timely response to customers’ needs – tools such as "Park Service Manager" (see Figure X) provide an end-to-end visualized self-service office park through capability decoupling, as shown in Figure X.

Figure 1: China Mobile’s Park Service Manager

The ultra-large-scale 5G private network covers 40 CATL factories in 8 locations throughout 6 provinces, supporting many 5G smart plant applications including quality inspection by machine vision, analysis of production safety, AGV (unmanned truck) for warehousing and logistics, etc. Results have been impressive so far:

• The whole project was delivered two months early, bringing more than $14 million dollars in business growth for CATL.

• Average service provisioning time was reduced from 3 days to 7 hours.

• Network data is aggregated and opened to customers through a single click, further enabling China Mobile to transform operations and maintenance capabilities into products for customers.

For operational excellence, AIS introduces the concept of zero-touch fault handling, realized by the integration of expert knowledge into platform-based orchestration policies. To achieve this, AIS strategically applies increasing levels of automation across the awareness, analysis, decision and execution stages, aiming to minimize human intervention and optimize fault resolution processes.

AIS’s Intelligent Incident Management Framework, shown in Figure X, revolves around embedding expert insights into the orchestration policies within the platform. This enables seamless fault handling across all stages, intending to achieve zero-touch operations. This approach harnesses the capabilities of AI and machine learning to detect, diagnose and resolve faults autonomously.

Figure 1: Intelligent Incident Management Framework

During the Awareness stage, AIS developed AI models and algorithms by using machine learning training and inference to establish dynamic thresholds. These thresholds aid in identifying abnormal events such as performance degradation, potential risks and suboptimal network health. Leveraging predictive models, AIS anticipates wireless CPRI optical link faults, home broadband and EDS optical fiber issues in advance, identifies risk before incidents, and combines with root cause analysis to eliminate risk before impact on services.

During the analysis stage, AIS employs AI-driven algorithms to identify fault propagation based on topology, time and spatial relationships. This AI-powered auto correlation significantly enhances the efficiency of fault detection across both single-domain and cross-domain scenarios. This transformation shifts from traditional expert-based methods to a machine and AI-driven paradigm, which optimizes NOC efficiency and reduces mean time to demarcation and creation of tickets.

In the analysis and decision stages, AI’s advanced root-cause analysis capabilities contribute to a reduction in unnecessary trouble tickets compared to conventional human analysis. Furthermore, self-healing mechanisms and auto-diagnosis address root alarm causes and enhance the autonomous handling of faults. These improvements lead to shortened mean time to resolution (MTTR) by accelerating corrective actions.

In the decision stages when an incident occurs, AIS evaluates the impact of network elements and convergent data on business and service. Factors such as the number of affected users, traffic loss and revenue implications are assessed to establish service impact severities. This analysis informs the prioritization of fault resolution efforts, ensuring high-priority fixes for incidents that impact revenue and customer experience.

Promising results

Successful implementation of intelligent incident management yields transformative outcomes for AIS and the autonomous network industry including:

• Fault auto-correlation ratio – achieving an impressive 76% fault auto-correlation ratio, with over 44,000 alarms being auto-diagnosed monthly by 2022; this figure is projected to increase to 0.7 million alarms per month by 2023, with an auto-diagnosis success rate exceeding 90%

• End-to-end automation – realizing 90% end-to-end process automation, resulting in a 20% improvement in MTTR

• Downtime reduction – realizing a significant reduction of over 10% in critical incident downtime

• Intelligent service impact – intelligently identifying service impact and fault handling priorities, ensuring end-to-end fault management is guided by experience assurance rather than solely fault severity

With the deployment of optical infrastructure networks and the rapid development of optical services, MTN is facing two major challenges. The offline resource confirmation process is long and efficiency is low, resulting in a long time to market (TTM) for services. In addition, many alarms must be addressed manually, which means root-cause analysis takes a long time, with two or three site visits required to locate the faulty node.

In this use case, MTN is developing an all-optical autonomous driving network that uses an intelligent management and control system as the core and introduces the new "T-AUTO" concept, which combines network inventory and routing diagrams/schematics to build an intelligent network with ultimate experience (see Figure 1). The network system is based on a transport digital map, which indicates all service routing, SLA indications and overall resource operations.

Figure 1: MTN’s All-optical AN with intelligent management and control system

The key capabilities of the network system are agile service routing, ultimate SLA guaranteed and time-saving ticket journey. In addition, the “Open to NaaS” (Network as a Service) capability provides industry customers with zero-contact, zero-wait and zero-fault experience, helping the network department improve maintenance efficiency and the marketing department increase operating revenue. The end user (the driver) receives high-quality service as SLA compliance is assured through automatic configuration and real-time awareness enabled via closed loop.

Resource closed-loop: The resource closed-loop uses rich network data such as real-time optical power, live network inventory, real-time link performance from infrastructure to make real-time decisions and handle the resource intents such as SLA assurance and fast fault handling within the autonomous domain (AD). Three types of assurance guarantee the SLA:

• Optical network resource assurance for resource readiness SLA – in the resource-check phase before service provisioning, through online resource planning and accurate prediction of service growth trends, resources can be reserved for new services in advance to avoid urgent capacity expansion.

• Optical network health assurance – by intelligently analyzing the deterioration status of optical fibers and cables, MTN can predict the fiber fault time in advance, handle the fault in advance and proactively perform O&M to avoid service interruption.

• Optical availability assurance – through the multi-dimensional evaluation and analysis of fiber and service availability, fiber cut impact, and service protection risks, this solution proactively identifies potential risks of fiber service availability, automatically generates warnings when threshold-crossing occurs and provides optimization suggestions.

In addition, a time-saving ticket journey is deployed. Through this capability, MTN achieves the correlation analysis of massive alarms and fault event-based identification.

Service closed-loop: The agile service provisioning function uses service models and multi-factor route calculation policies to recommend routes based on users’ differentiated requirements, greatly improving the success rate of one-time service provisioning.

Business closed-loop: With the Open to NaaS function, the NMS and online bandwidth domain are connected, and network capabilities are opened to marketing departments and enterprise users, including online bandwidth adjustment for private lines and service SLA performance visualization. Through capability openness, MTN is able to enhance user loyalty.

Promising results

Based on the T-AUTO concept and functions, MTN has significantly improved network planning and O&M efficiency:

• During service provisioning, time-to-market is shortened from days to minutes

• Network reliability is improved to 99.999%

• The number of invalid O&M orders is reduced by 75%

• Troubleshooting time is shortened from 8 hours to 15 minutes

In response to the challenges posed by the expansion of its 5G network, Telefónica Brazil has implemented an automation solution that simplifies and streamlines the integration, configuration and provisioning of the network transport and mobile access layers. The solution performs end-to-end configuration and validation of the network, enabling seamless provisioning of equipment and services. By automating these complex processes, the solution enhances the quality of network implementation and expansion while reducing the probability of errors. This innovative solution is unique and currently not available anywhere else.

Telefónica Brazil is facing a significant challenge in rapidly expanding its network to meet the growing demand and vast expanse of the Brazilian territory, particularly with the widespread deployment of 5G technology. The conventional processes for integrating and configuring mobile network equipment are no longer adequate to meet the strict deadlines and quality standards required for this expansion. The company has developed an autonomous configuration system to streamline the configuration and provisioning processes and incorporate all business requirements.

To tackle these challenges, some of the key capabilities include:

• Consolidating the business requirements of each area, which significantly reduces the time required for the whole configuration and provisioning process

• Establishing an automated workflow for end-to-end activation, ensuring consistent and error-free results

• Enhance quality of service in delivering services

• Standardize provisioning activities across Brazil

• Introduce online testing, eliminating the need for manual tests that took days in some areas

The solution automates the configuration and provisioning processes while considering and respecting all the business rules on the network. The solution analyzes the characteristics of each region of Brazil, which has equipment from different manufacturers, different hardware and software versions, different types of transmission, and while mixing the legacy network with new technologies. It also integrates the deployment, engineering, field teams, operation and maintenance, change management, network performance and technology areas.

A key differentiator of this solution was the centralization of data from all areas involved, enabling assertiveness in the configuration and customized access for each area. The system’s scalability is a key advantage, since it was specifically created to aggregate the use cases of the network, with access to information managed by group of users. Consequently, it has greatly improved the internal user experience.

Interoperability is another strong aspect of the project, as the solution works with more than 20 models of equipment and dozens of variations and configurations created in different regions of the country. It is integrated with the trouble ticket system and scheduled tasks management system. A series of APIs are available to integrate with and connect with other systems to obtain the necessary information for the entire chain of deployment and configuration of the transport network.

The certification and auditing of configuration and provisioning activities is an important feature of the project, as it provides traceability and certification that all configurations performed by automation were successful. All information is recorded in a database, making it possible to search for any configuration performed by automation. The result of this auditing process brings detailed data, such as whether the configuration was correctly performed on the specific day of the activity. At all stages of deployment, auditing can be used to ensure process quality and compliance.

Innovation is another distinguishing factor of the project, as it is constantly evolving. It was designed with an open systems architecture, allowing technicians and developers to implement use cases and embrace new automation ideas as technology progresses. For instance, the current benefits have already been applied to meet diverse network demands, effectively serving both mobile and fixed networks, and even providing high-speed internet services. Future plans include integrating with RF equipment to configure end-to-end services.

Promising results

Telefónica intends to have a zero-touch autonomous network zero-touch by 2024. With this, any model of equipment when connected to the network will be identified and implemented following all standards and without any human intervention.

The solution has made a significant impact on end customers by delivering services of higher quality, speed and reliability. Also, it guarantees the traceability of processes, ensuring that the end-to-end activation process is streamlined and optimized. The program has resulted in impressive outcomes, including:

• Over 72,000 tests performed

• Savings of more than 42,000 hours of work (equivalent to 5,900 workdays)

• Time to activate a box on the network has been reduced from 32 days to less than 24 hours, resulting in faster service delivery, with higher quality and delivery guarantee

• Activities scheduled at night are now performed during the day; this new way of work assures results with network audit requirements

• An estimated 25% reduction in network alarms and 30% reduction in rework