RAN-intelligent controller

Bringing Intelligence to the RAN

RAN Intelligent Controller: Integrating AI with RAN

RAN Intelligence

Introduced in 2019, Accelleran’s Near Real-Time RAN Intelligent Controller (RIC) platform is essential for network operators seeking to reduce infrastructure and operational costs, enhance network efficiency, and improve business agility. It also opens new revenue opportunities through customized services, network slicing, and indoor location services.

Accelleran’s dRAX-RIC stands out as a premier choice for operators and integrators aiming to leverage Open real-time RAN data and control to achieve superior RAN Automation. This platform supports the development and integration of AI-driven xApps, significantly enhancing RAN capabilities.

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AI-Enabled Apps

Created by Accelleran and third parties

Engineered for seamless third-party app onboarding, our RIC platform and associated apps enhance automation, lowering the total cost of ownership (TCO) for mobile operators while boosting customer experience and service quality. With user-friendly xApps boilerplate code and comprehensive APIs, developers can swiftly create unique xApps and effectively integrate RAN intelligence into their operations.

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A RAN Intelligent Controller (RIC) platform is a software-defined component of the Open Radio Access Network (O-RAN) architecture. It provides centralised control and management of the RAN elements, optimising network performance and resource utilisation through the deployment of xApps (near real-time applications) and rApps (non-real-time applications).

xApps/rApps deployed on the RIC include:

  • Optimisation: Enhancing network performance by dynamically managing resources.
  • Automation: Automating network operations and reducing manual interventions.
  • Programmability: Allowing third-party developers to create applications (xApps/rApps) that can run on the RIC to introduce new functionalities and services.
  • Analytics: Collecting and analysing real-time data from the RAN to provide insights and enable proactive network management​.

Apps deployed on Accelleran’s RIC improves network performance by using AI and machine learning algorithms to analyse real-time data and make decisions that optimize resource allocation, reduce latency, enhance throughput, and improve overall user experience. It allows for dynamic adjustments based on current network conditions​.

AI plays a crucial role in RIC xApps/rApps by enabling advanced data analytics and decision-making processes. AI algorithms analyze vast amounts of real-time data from the RAN, allowing for predictive maintenance, anomaly detection, and intelligent resource management. This leads to more efficient and resilient network operations​.

Some example x/rApps for RIC include:

  • Interference Management: Mitigating interference between cells to improve signal quality.
  • Load Balancing: Distributing network traffic evenly across available resources to prevent congestion.
  • Energy Savings: Dynamically adjusting power usage based on network demand to reduce energy consumption.
  • Quality of Service (QoS) Management: Ensuring that different types of traffic receive the appropriate level of service based on their requirements​.
  • xApps: Near real-time applications that run on the Near-Real-Time RIC (Near-RT RIC). They are responsible for tasks that require low latency, such as interference management and load balancing.
  • rApps: Non-real-time applications that run on the Non-Real-Time RIC (Non-RT RIC). They handle tasks that can tolerate higher latency, such as long-term network planning and policy management​.
  • Near-RT RIC: Operates with a latency of less than one second and is responsible for real-time control and optimization functions using xApps.
  • Non-RT RIC: Operates with a latency of more than one second and manages non-real-time tasks using rApps. It provides policy guidance and long-term data analytics to the Near-RT RIC​.

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