Despite huge investments in 5G, network operators are still highly reliant on revenues from traditional voice and broadband data services and are struggling to increase ARPU. With 5G Advanced around the corner, they will need to continue investing heavily in new network infrastructure for many years to come, despite rising debt levels. As a result, the business models of many of these operators risk becoming unsustainable unless major changes are made.
Overcoming Operator Challenges
To survive financially and benefit from their 5G investments, operators need to develop new revenue streams while reducing OPEX costs. To achieve this, they need to radically transform the way they operate their networks. Instead of a fixed architecture, a fully flexible and agile service platform is required with the capability of delivering a wide variety of services on-demand. This means that networks need to be cloud-based, software defined, highly programmable and ultimately completely automated. By making their networks agile, operators will be able to deliver a huge variety of services with user experiences and connectivity dynamically tailored to individual use cases, or even individual users. Over the next few years, Counterpoint Research believes that AL/ML driven automation will play a critical role in facilitating this business model transformation, allowing operators to develop new revenue streams while significantly reducing OPEX costs.
Transition to L4 Automation
Autonomous networks are networks that can run with minimal (and ultimately zero, i.e. zero-touch) human intervention while leveraging technologies such as AI, machine learning and edge computing. Operators have already started the journey to automation, which they plan to implement in stages. For example, most Tier-1 operators have reached either Level 2 or Level 3 and many plan to reach Level 4 automation by the end of 2025/26.
Compared to L3 automation, L4 offers many new features and capabilities. With L3 networks, O&M updates are implemented into the network manually and run to gauge the network’s response. This typically involves multiple iterations. In contrast, L4 automation offers the capability of using a digital twin, i.e. a virtual or digital copy of the physical network. This is essentially a simulation environment which enables network changes to be run hundreds of times in isolation, enabling the optimum parameters to be identified before they are implemented into the physical network.
L4 automation also enables improved data collection processes allowing operators to have greater visibility into the network. For example, L4 offers the ability to collect more data from a base station compared to L3. L4 can also collect data more frequently. As a result, L4 automation can offer predictive and preventative capabilities, where potential faults are identified and rectified, thus ensuring that base stations are always online. Operators typically do not want to implement automation for everything, with most focusing on two processes: network deployment and fault monitoring and maintenance.
Huawei’s RAN Digital Twin
Huawei has developed a RAN Digital Twin System (RDTS) which is used in conjunction with its IntelligentRAN architecture to leverage the new capabilities of L4 automation. Central to its operation are the following four new innovative features:
IntelligentRAN L4 i-series solutions
In early 2023, Huawei launched its 3-layer, hierarchical IntelligentRAN architecture which has been deployed to date by more than 30 operators worldwide. IntelligentRAN enables the key capabilities of L4 autonomous networks to be realised. This includes intent-driven networking, intelligent sensing, multi-target decision optimization and proactive/predictive O&M. At its recent Global Mobile Broadband Forum in Dubai, Huawei announced three additional L4 i-series solutions:
Operator Examples
In recent months, Huawei has demonstrated the benefits of using the RDTS system operating within its IntelligentRAN architecture with several of its operator partners. For example:
Viewpoint
The business models of many network operators risk become unsustainable unless they fully embrace automation. L4 autonomous networks will allow operators to deliver an experience that is far better than with previous generations of mobile networks. With L4, intent-driven networking replaces policy-based network management, deterministic service assurance replaces best-efforts approaches while proactive O&M (leveraging predictive/preventive capabilities) is used instead of responsive O&M. Together, these new capabilities will enable operators to significantly reduce OPEX costs as well as generate new revenues.
However, there are still challenges ahead. Standards, or specifically a lack of collaboration among standards bodies and open-source groups, is perhaps the biggest challenge. In particular, the industry needs to define data standards and formats. Another challenge is transforming company culture and skills, for example, with respect to network operations personnel. Linked with culture and skills is a lack of a common understanding of key technologies: for example, is there a precise, industry agreed definition for intent-driven management? The development of open APIs will also be very important. Collaboration with industry and ecosystem partners, including device manufacturers, equipment suppliers and developers will be essential in order to bring the economies of scale needed to benefit all players.
This blog is sponsored by Huawei.
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