Cloud-ready 5G Architectures Demand Automation in Operations and Optimization

5G success relies heavily on the performance and interoperability of the radio access network (RAN) and technology-enabled subscriber handsets. As RAN architecture evolves to support 5G capacity and latency requirements, new and higher bandwidth frequencies require the deployment of more and more small cells–exceeding traditional LTE cells fivefold.

Address Traditional and New Challenges with Specialized and Problem-specific Artificial Intelligence RAN Datasets

Traditional RAN Problems Intensify with 5G:
  • Coverage
  • RF Overshooting
  • UE Capability
  • Neighbor Cell Relations,
  • Antenna Cabling Errors
New Problems Surface with New Standards:
  • Carrier Aggregation
  • Ultra Low Latency
  • Distributed RAN Components.

Think RAN-forward with Omnis RAN Automated Analytics and Automated Optimization Modules

With manual tuning of capacity, interference, and coverage objectives increasingly cost prohibitive, new, comprehensive workflows that can analyze information quickly and confidently guide next actions are needed. Omnis RAN Automated Analytics and Automated Optimization modules meet this objective to enable informed 5G RAN evolution.

Offering carrier service providers a customizable and holistic approach for network growth, business transformation and profitability, the Omnis RAN solution features distinct modules designed to address specific 5G RAN deployment challenges.

Omnis RAN Automated Analytics and Automated Optimization Modules provides unmatched insight

Solution Highlights

Support for Third Party Systems

Highly scalable standalone offerings designed to support existing automation systems and feed third party data lakes.

Compatible with NETSCOUT Tools

Omnis RAN Automated Analytics and Automated Optimization modules provide seamless integration and drill-through capabilities for advanced troubleshooting of RAN issues.

Greater Accuracy for Key Initiatives

Improve geolocation accuracy for superior service quality and monetization studies with correlated high-definition data and error-detection auditors.

Modules