15 June 2021
MNOs are looking to OpenRAN to take control of the 5G network by transitioning to a flexible and scalable architecture. To truly realize its benefits, MNOs are also rethinking how they control, operate, and manage the RAN. Extreme network automation is at the heart of this approach, with the RAN Intelligent Controller (RIC) in turn proving to be foundational to achieve this extreme automation and provide fine grained, use case driven control and management of the RAN resources.
Analysys Mason has conducted a dedicated survey of Tier 1 and Tier 2 MNOs, as well as alternative network providers worldwide, to assess the current state of the industry’s view on the RIC platform, with a specific focus on the near-real-time (near-RT) RIC. The survey focused on many areas relating to deploying the near RT RIC, including the business and commercial rationale, use case priorities, deployment timelines and the role of artificial-intelligence and machine-learning.
The analysis of the survey results have all been captured in this paper. Key participants within the TIP RIA subgroup highlighted the below data points:
- Richard Mackenzie at BT: “About 35% of the MNOs in the survey are planning to use the RIC to manage all Open RAN operations, and a further 20% are considering specific Open RAN use cases for the RIC whilst about 31% of the MNOs are planning to deploy the near-RT RIC by 2023, and a further 31% by 2026.“
- Carlos Ubeda at Vodafone: “About 23% of the MNOs said AI/ML is a critical enabler to automate the near-RT use cases, while about 46% are evaluating the role of AI/ML in near-RT RIC. MNOs chose QoS-based radio optimization, real-time video optimization and massive MIMO optimization as the top three use cases to use AI/ML.”
- Vish Ponnampalam at Facebook: “About 68% of the MNOs said portability of xApps across different near-RT RIC platforms is an important or very important capability. Multiple RIC platforms, both open source and proprietary, will probably emerge from different vendors and ecosystems.”
The study also underscores how ecosystem collaboration, control and governance is critical to accelerate the commercialization of near-RT RIC, and the broader Open RAN and RIC.