VIAVI NITRO Location Intelligence (LI) End-to-End Mobile Network Optimization Software
Software that uses geolocated subscriber data and a digital twin engine to automate the full mobile network optimization lifecycle.
- Step 1
- Finding areas with problems: automatically detect areas with bad performance affecting the subscriber QoS
- Step 2
- Network optimization based on digital twin engine. Automatically validates all possible antenna changes in the network and provides a gain analysis with the best combination of parameters
- Step 3
- Once the changes have been implemented in the network, NITRO LI helps you generate assessment reports automatically
Overview
VIAVI NITRO Location Intelligence (LI) is software for 5G and mobile network optimization. It covers the whole optimization lifecycle: finding problem areas, working out a configuration plan and producing acceptance reports. New technologies and denser site deployments make network optimization slow and complex. NITRO LI automates these steps and bases them on what subscribers actually experience.
Finding problem areas
NITRO LI uses geolocated subscriber data to find areas where performance is poor and subscriber quality of service suffers. Examples include low quality, poor throughput and bad voice MOS. KPIs are measured from the subscriber's point of view rather than the network's.
Digital twin optimization
The same raw data feeds a digital twin engine that checks every possible antenna change in the network. The engine then gives a gain analysis showing the best combination of parameters for a strong RF baseline. A score evaluator applies goals and constraints across metrics such as average and coverage RSRP and RSRQ, spectral efficiency, estimated drops and estimated blocks. Optimization methods include hill-climbing and evolutionary algorithms.
Assessment reporting
After the changes are made in the network, NITRO LI generates before/after assessment reports for the affected areas automatically.
Key Features
- Fully automated optimization lifecycle
- KPIs from the subscriber point of view rather than the network point of view
- Digital twin antenna optimization engine improving throughput, drop rate, coverage and quality
- Automatic detection of areas with poor performance affecting subscriber QoS
- Validation of all possible antenna changes with gain analysis of the best parameter combination
- Automatically generated before/after assessment reports
- Score evaluator with configurable goals and constraints
Specifications
| Step 1 | Finding areas with problems: automatically detect areas with bad performance affecting the subscriber QoS |
|---|---|
| Step 2 | Network optimization based on digital twin engine. Automatically validates all possible antenna changes in the network and provides a gain analysis with the best combination of parameters |
| Step 3 | Once the changes have been implemented in the network, NITRO LI helps you generate assessment reports automatically |
| Input data | Geolocated subscriber insights |
|---|---|
| Problem areas detected | low quality, bad throughput, bad Voice MOS |
| KPI perspective | Subscriber point of view (rather than network point of view) |
| Metrics improved |
throughput, drop rate, coverage, quality
Digital twin antenna optimization engine
|
| Score evaluator metrics (goals and constraints) | Average RSRP, Average RSRQ, Coverage RSRP, Coverage RSRQ, Spectral Efficiency, Spectral Efficiency Coverage, Estimated Drops, Estimated Blocks, RERP, RERQ, Calls Switched On |
|---|---|
| Optimization algorithms | Hillclimber, evolutionary algo |
| Engine components |
Metric Generation Engine, Physical Parameter Change Modelling, Score evaluator, Optimization
System state prediction compared with system state 'ground truth' from NITRO GEO
|
| Ground truth data source | NITRO GEO |
| Reporting | Automated before/after reports |
Specifications are taken from the manufacturer's documentation. See the datasheet for complete and current values.
Applications
- 5G network optimization
- RAN antenna parameter optimization
- Subscriber experience analysis
- Network change acceptance reporting
- RAN energy savings