Cognitive Optimization area provides capabilities to help customers to get the most out of their network investment, with the focus on network performance and end user experience. This is provided in several software features by
- Enabling RAN optimization based on correlation of CM and PM information. Additionally, automatic classification of cell issue patterns is also available by means of deep learning models, as well as uplink interference pattern recognition. Root Cause Analysis can be also performed in this pattern recognition.
- Leveraging on the geolocation of call traces, comprehensive digital maps can be used for analysis, reporting and proposal of changes. Main use cases supported include Call Trace parsing, assembling and geolocation, raster plot with KPI calculated from traces, RDT/MDT support, polygon support, etc. Support environmental goals of CO2 reduction using driveless techniques
- Network parameter changes are proposed based on AI models that learn from the live network using the latest technologies to deliver real improvements.