Dynamic 5G Network Slicing

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AI is useful for data analysis and forecasting, but neural networks take too long to operate during traffic transmission. The algorithms do not have enough speed to optimize processes at the user and control level. Therefore, the optimal option for using the technology is at the management level.



Machine learning algorithms can predict traffic patterns and adjust slices so that they do not consume unnecessary resources and provide the performance needed for specific applications.

AI systems can monitor network areas in real time venezuela telegram to make adjustments to maintain QoS.

If a critical application experiences increased latency, AI can automatically reallocate resources from less important virtual areas. For example, neural networks can “shift” bandwidth from a streaming app to an autonomous driving system.



Network planning
AI can help with the placement of new towers. Neural networks can analyze 3D maps of the area, population density, mobile network performance, and other data to identify areas where demand for quality communications is growing.

You can also identify specific locations for new towers based on terrain, infrastructure, potential interference, and proximity to users. Before actual deployment, you can simulate different scenarios to calculate how new towers will impact coverage.



Energy management
GSMA estimates that telecom operators spend around 20-40% of their operating costs on electricity, mostly on mobile and fixed networks. At the same time, in the last few years, the growth in electricity costs for major players has outpaced sales growth by around 50%.