Operators faced significant obstacles in maintaining consistent network performance across RAN components sourced from multiple vendors. Each vendor implementation behaved differently, making it difficult to predict performance under load or compare solutions fairly. The absence of a unified benchmarking framework limited visibility into critical E2 interface characteristics, including scalability, latency, throughput and reliability.

Additionally, uneven traffic distribution caused congestion and overloaded cells, leading to reduced throughput and degraded user experience. Without proactive traffic management, operators were forced to rely on reactive measures, increasing operational complexity and risk to service quality.

The primary objective was to establish a standardized, repeatable approach to measure and improve network performance across O-RAN environments. Specifically, the program aimed to:

Our team at HCLTech, delivered a comprehensive solution built around two key components: Benchmarking and Advanced Traffic Steering.

The Benchmarking xApp provided a structured framework to test E2 interoperability, scalability and performance across different RIC platforms. It enabled controlled testing of KPIs such as subscription latency, control latency, throughput and resource utilization, allowing operators to identify system bottlenecks and integration issues early in the lifecycle.

Complementing this capability, the ATS application leveraged AI and machine learning to monitor UE and cell-level KPIs in connected mode scenarios. By predicting congestion and capacity utilization trends, ATS proactively executed optimization actions such as handovers and load balancing, improving overall system throughput and network efficiency.

The solution was deployed as both xApp and hybrid variants on OSC and VMware RIC platforms and was rigorously validated through extensive multi-vendor testing with ecosystem partners in controlled lab environments.

Delivered measurable improvements in network performance visibility and traffic optimization across multi-vendor O-RAN environments.

Future efforts will focus on advanced conflict mitigation strategies between multiple rApps and vendors. HCLTech plans to enhance AI/ML workflows for tighter standards alignment, expand KPI visualization through advanced dashboards and further scale E2 nodes and subscription counts. The long-term goal is to mature ATS to TRL-9 readiness and support broader scenarios, including idle-to-connected mode traffic management.