RAN Analytics
Optimizing 5G Network Performance
Gain critical insights with advanced RAN analytics and automated complaint resolution to enhance 5G RAN and Open RAN performance. Leveraging AIOps, the solution enhances network performance, providing ticket validation, prioritization and prediction to significantly reduce the time and effort network engineers spend investigating and resolving technical issues.
Find out how you can optimize your 5G RAN now
RADCOM RAN Analytics solution determines and swiftly resolves issues impacting subscribers’ quality of experience. The solution creates enhanced value for customers by empowering teams with a deep understanding of service degradations, and geolocation data. This offers insights into precise areas with low service quality or radio coverage. The AIOps-driven insights help optimize new radio sites throughout the roll-out process, before, during and after deployment, ensuring a proactive, and seamless end to end user experience.
Predictive Complaint Resolution
RADCOM RAN Analytics infused with generative AI (GenAI) automates multiple service ticket investigation and resolution tasks. It includes background workflows that interface with service ticket platform to process tickets assigned to the network. Validating tickets, it correlates RAN with core network faults in subscriber KPIs. The solution also predicts the next subscriber complaint on the network, improving customer service.
Key Capabilities
The solution provides engineering insights into key performance metrics: such as reliability, and signaling overhead, saving the operator time performing root cause analysis (RCA) methods to detect anomalies. It is vendor-agnostic and can monitor and correlate multiple-vendor RAN feeds and even correlate between them.
Offers in-depth analysis of the RAN performance in real-time
Prioritizes customer-affecting degradations to maintain QoS
Correlates core and RAN data into subscriber (IMSI-based) insights
Helps reduce trouble ticketing workloads, driving down costs
Detects and determines the root cause of RAN degradations
Identifies similar issues across
all subscriber bases
Benefits
Offers visibility and end-to-end monitoring
RADCOM RAN Analytics together with RADCOM’s Core Analysis solution enables telecom operators to correlate the core data with the RAN data together to gain deep subscriber (IMSI-based) insights. These are critical for understanding the real customer experience as it provides hundreds of subscriber-centric metrics and KPIs for end-to-end network optimization and advanced troubleshooting.
Offers deep insights with Integrated AIOps capabilities
RADCOM RAN Analytics integrates RADCOM AIM which includes artificial intelligence and machine learning (AI/ML) capabilities to smartly analyze and provide real-time automated insights to resolve customer-impacting issues and save engineering resources. These include impact analysis, sleepy cells analysis and identification, capacity forecasting and utilization and root cause analysis.
Improves ticket resolution
Reducing the burden of unprioritized tickets waiting attention, RADCOM RAN Analytics with its Predictive Complaint Resolution improves ticket resolution time and enables prioritization of tasks based on subscriber impact. This also allows proactive mitigation of subscriber issues before they exacerbate, ensuring engineers can identify and can concentrate on the worst offending cells or geographical regions.
Detects root cause of RAN degradations
Engineers gain insights into root causes of RAN degradations through an automated process that monitors and measures quality metrics and detects specific issues. The solution alerts engineers to RAN performance degradations and utilizes decision trees enriched with AIOps to rapidly, automate issue resolution
Integrates with business operating systems
RADCOM RAN Analytics automates integrates with business operating systems, and includes background workflows that interface with platforms like ServiceNow. The solution helps correlate network faults in the service assurance subscriber KPIs and views the cells with the highest impact, recommending fixes and prioritizing tasks.
