RAN AIOps
Optimizing 5G Network Performance
Automate Network Operations with RADCOM RAN AIOps
What is AIOps in RAN?
AIOps in RAN (Radio Access Network) applies artificial intelligence, machine learning, and big data analytics to enhance, automate, and simplify the management of increasingly complex mobile networks. It shifts from manual oversight to intelligent automated processes and helps optimize and manage mobile radio network functions. In RAN and Open RAN environments this reduces operational costs, improves efficiency and deliver superior quality of experience to subscribers.
How Can RADCOM RAN AIOps Help You?
RADCOM RAN AIOps leverages RAN domain expertise and AIOps (artificial intelligence for network operations) to automate RAN optimization and proactively ensure RAN performance. Covering a wide range of customizable use cases, the solution combines AI and machine learning (ML) with big data and advanced analytics to enhance RAN network operations. This includes monitoring, event correlation, automated root cause analysis, anomaly detection categorized by error type, and more for faster and more accurate problem resolution and enhanced performance. The solution also supports bringing your own analytics container (BYOAC), providing tools for comparing different ML model results so users can find their preferred model.
Benefits
Real-Time Analytics
Automation
Diagnostics
Planning
Geolocation data
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Features
Automated Root Cause Analysis
RADCOM RAN AIOps leverages automated root cause analysis (RCA) to detect and resolve network issues, prevent service degradation and reduce operational costs. By continuously monitoring KPIs and user experience metrics at the cell level, RADCOM identifies anomalies and pinpoints fault domains and sources. This enables network teams to distinguish between normal and abnormal behavior, accelerate resolution, and ensure service quality.
Automated Complaint Validation and Prioritization
RADCOM RAN AIOps uses real-time data correlation to quickly detect and resolve quality impacting issues. The solution validates and prioritizes complaints based on subscriber impact, leveraging geolocation and service degradation insights to pinpoint low-performance areas. It identifies recurring issues across the network and reduces ticketing workloads to boosts customer satisfaction.
