Zinkworks Network Positioning Prediction rApp

NPP rApp excels in providing accurate multi-trajectory forecasts by processing positioning data from a wide array of network users and devices. This comprehensive framework integrates data from various sources to generate detailed predictions about user movements and distributions within cellular networks. NPP ensures that the resulting time series data is smooth and precise by leveraging advanced encoding, decoding, and feature engineering techniques. This capability allows network operators to anticipate and manage user distribution more effectively, optimising network resources and improving service quality. Accurate forecasting of user trajectories enhances the overall network efficiency and contributes to better user experiences by preemptively addressing potential congestion issues.

NPP optimises power management by predicting the User Equipment (UE) distribution connected to cells. By accurately forecasting user movements and their concentration around various cells, the NPP enables network operators to dynamically adapt transmission (TX) power. This adaptive power adjustment minimises unnecessary power consumption, especially during low-traffic periods or less densely populated areas. Significant energy savings can be achieved by reducing the power levels of base stations where fewer users are connected. This lowers operational costs and contributes to a greener, more sustainable network operation. The NPP rApp ensures efficient power usage while maintaining optimal network performance and user satisfaction.