Open RAN intelligent controller enables differentiation/optimization

Open RAN intelligent controller enables differentiation/optimization

New Products |
By Jean-Pierre Joosting

Mavenir has announced the availability of its O-RAN alliance Radio Access Network Intelligent Controller (RIC), a next-generation network intelligence offering for Open RAN. The Mavenir O-RIC enables the creation of differentiated services through open APIs, which enable intelligent closed-loop end-to-end network tuning to optimize network performance, increase cost efficiency and maximize the user experience. The O-RIC offers Network Intelligence as a Service (NIaaS) that provides deep, fine-grained insights about the network and enables building systems with advanced state of art intelligence. Open RAN networks can also now generate new class-of-service revenue streams by adaptively reacting in near-real time to dynamic changes in network, traffic, and load patterns. The O-RIC is currently in deployment with two, tier one Communications Service Providers (CSPs).

Traditional RAN networks currently use area wide Self-Organizing Network (SON) models for exercising Radio Resource Management (RRM) and configuration management optimization decisions at a per-cell level. They rely on single control loop, leverage key performance indicators (KPIs) and analytics for such control decisions at non-real time (Non-RT) granularities.

The O-RIC surpasses the capabilities of SON with two control loops:

  1. Non-RT O-RIC — Typically deployed in a centralized cloud, it builds advanced Machine Learning (ML) algorithms using long-term RAN data to define dynamic and adaptive policies to control and optimize network performance and configuration management decisions. Non-RT RIC can also be used in existing legacy networks, adding another performance layer through ML for policy control.
  2. Near-real time (Near-RT) O-RIC — Deployed at or towards the edge, it uses a low latency control loop that optimizes RAN activity at both the cell and individual user equipment (UE) level by hosting trained Artificial Intelligence (AI) and ML applications to infer and control Open RAN

A business results tool, the O-RIC enables intent-based decisions by setting granular performance targets—at the cell or even individual UE level—to generate business outcomes, such as the generation of additional revenue (enabling an SLA that generates a premium service), the reduction in network cost through the optimization of resources (energy savings, spectral efficiency, etc.), or the improvement of the end user experience (by improving throughput, reducing latency and connection drops, and expanding coverage). The NIaaS signature framework of the RIC accomplishes this goal by offering fine-grained predictive intelligence and advanced analytics about the RAN to third party applications (rApps and xApps), integrated with the O-RIC, towards optimizing the network performance.

Mavenir’s O-RIC shifts control from the vendor ecosystem to the operator by delivering an Open API framework that allows the implementation of standards-based rApps and xApps for different business outcomes, such as energy savings, traffic steering, massive MIMO optimization, spectral efficiency improvements, and RAN slice assurance. Proprietary radio access solutions limit the choice to what their vendor has to offer and open up the network to fine-grained per user data-driven optimization. With Mavenir’s RIC, applications can be developed by an in-house team or purchased in an “app store” from any Open RAN compliant third party.

“Creating real business value for next-generation Open RAN networks requires deep telco domain expertise and a disruptive approach to network intelligence,” said Brandon Larson, SVP and GM of the Multimedia Business Unit at Mavenir. “As a pioneer in cloud-native solutions at a massive scale, Mavenir is leading the way with award-winning Open vRAN, layered with O-RIC AI and ML algorithms and applications, which create operator customizable business outcomes based on target objectives to solve unique business problems and give control of the network back to the CSP.”


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