RAN Monitoring: Vital for End-To-End Assurance
RADCOM ACE, our end-to-end assurance solution, includes Radio Access Network (RAN) monitoring providing operators with complete network visibility. As an operator, it enables you to genuinely understand the root cause of any network degradations and apply corrective actions to ensure a superior customer experience for 4G and 5G.
RAN data includes core metrics such as Packet Jitter, Packet Loss, Timeouts, Throughput, and Connection Release Cause that can all be collected and measured. As part of an end-to-end monitoring solution, these metrics, combined with data from the core, such as IMSI and IMEI data, provide real-time subscriber analytics and customer-focused analytics.
Benefits to operators:
- Real-time visibility into RAN issues to troubleshoot effectively
- Helps engineers plan, optimize and deploy new greenfield RAN for 5G
- Covers all RAN spectrums from low, medium (C-Band), and high band (mmWave)
- Monitors RAN performance to detect the root cause of degradations
- Includes important RAN data in your overall service assurance solution
Gain Complete RAN coverage: C-band to Millimeter-wave
As radio-related issues critically impact the customer experience, RADCOM ACE smartly monitors Key Performance Indicators (KPIs) for the radio access network. Both the control plane and user plane are covered. As cells continue to be deployed, you can monitor the quality, coverage, and subscriber usage to see if these new cells have performance issues that need to be optimized.
Monitor and optimize mmWave performance
RADCOM ACE can help you plan the optimal position for mmWave sites and then plan the neighboring cells. Using RADCOM’s solution, engineers can see each cell’s different parameters, how they are performing, and handovers.
RADCOM’s solution helps operators ensure their mmWave deployments by continually monitoring:
- Loss of service
- Low throughput
- The control plane and user plane.
Built-in Artificial intelligence and Machine Learning
RADCOM ACE utilizes built-in machine learning capabilities to automatically deliver RAN insights, saving the operator time performing root cause analysis and detecting anomalies. Some AI/ML use cases for the RAN are:
- IMSI journey
- Identify data hoggers
- Cell outage predictions
- Discover coverage holes
- Ping-pong effect identification
- Anomaly Detection
- Automated Root Cause Analysis.