In today’s rapidly evolving O-RAN telecommunication environments, network reliability and operational efficiency are critical to sustaining continuous service delivery and minimizing downtime, network availability requirements are becoming increasingly stringent, with a baseline expectation of 99.99% uptime to support mission-critical applications and meet user experience. The current network infrastructures built on LLS-C1 and LLS-C2 often struggle to effectively scale, handle desired number of radio units, handle increasing data loads, complex traffic patterns, and the demand for real-time analytics, which impedes timely fault detection and corrective action. The LLS-C3 topology offers a transformative architecture designed to enhance network resilience, scalability, and automation capabilities. However, the deployment of LLS-C3 topology has not kept pace with the accelerating need for predictive maintenance frameworks that leverage automated fault prediction and self-healing mechanisms. Without the urgent implementation of LLS-C3 topology, operations risk prolonged network outages, increased maintenance costs, and suboptimal resource utilization. This delay hinders the ability to integrate advanced network automation and predictive maintenance solutions that rely on robust, adaptive network structures. Consequently, the lack of LLS-C3 deployment poses a significant barrier to achieving proactive network management, which is essential for reducing unplanned downtime and optimizing operational performance in increasingly complex network environments.
This project has following primary objectives
Distributed Solution Integration: Deployment of a distributed network solution that seamlessly integrates with both real-time and non-real-time RAN Intelligent Controllers (RIC) within the LLS-C3 topology, enabling advanced network transformation. Complex Task Automation: Efficient handling of complex operational tasks such as aligning and matching delay profiles between the O-DU (Distributed Unit) and O-RU (Radio Unit) across intricate and heterogeneous operator network layouts. Performance and Latency Prediction: Leveraging predictive analytics to forecast network performance and latency, enabling proactive adjustments and optimization to meet stringent service level agreements (SLAs). Enhanced Network Automation: Empowering network automation capabilities to facilitate self-configuration, self-optimization, and self-healing processes, thereby reducing manual intervention and minimizing downtime. Scalable Network Transformation: Supporting scalable and resilient network transformation that addresses growing data demands and evolving infrastructure, ensuring the network consistently meets or exceeds the 99.99% availability benchmark.