How to Effectively use the potential of 5G: Network slicing and the role of al and machine learning

May 6, 2022

The irruption of 5G represents infinite potential. In fact, thanks to this new technology, communication service providers will be able to offer new services to their users. Is your telecommunications company ready to take the big leap? Can combining network slicing with AI and ML help you do that?

What Is Network Slicing?

Network slicing consists of enabling the rapid generation of logical and virtual networks based on physical technical infrastructures. It is a procedure that can work even on demand creating networks intended to serve various targets or clients.

The network slicing means that the CSP divides the 5G network into smaller segments in order to dedicate each of them to specific tasks. The benefits this brings to the operator are obvious, as it provides more efficiency, speed and flexibility.

Network slicing applies virtualization to radio access networks (RANs) and backhaul and carrier core networks. With this, the providers can guarantee a minimum performance in the connections or the preferential delivery of shipments from specific devices.

How To Implement Network Slicing

The 5G network is divided into segments that work independently and securely. Each of these slices is dedicated exclusively to a different service, providing them with custom requirements for speed, latency, and security.

Each network segment can be dedicated exclusively to one client or shared by multiple users. Indeed, it is possible to extract a portion of the cell’s capacity and treat it as a separate logical entity.

The efficient management of network segments requires having an OSS and a BSS capable of providing 100% automated processes. Thanks to them, an optimized provision of resources is guaranteed throughout the process.

The most convenient solution is to work through virtual networks based on the cloud. This ensures that these can be used by various equipment providers without losing the highest rates of speed and latency in real time.

QoS: The Essence of Network Slicing

One of the main objectives of segmenting the 5G network is to provide a better quality of service. The novelty here is that users and providers have a different concept of network slicing.

  • vertical divisionallows us to manage the network to provide a better quality of service.
  • On the other hand, the segments of the network complement the shared resources.

Harmonizing both perspectives is the task of AI and machine learning, the use of which will allow us to control several devices at the same time.

Al And Machine Learning – Key To Implementation

If we want to ensure that network slicing works correctly, we must bet heavily on the use of artificial intelligence (AI) and machine learning (ML).

  • AI-based tools provide the agility and flexibilitythat network slicing needs for error-free operation.
  • ML makesapplication management much easier, as it offers such interesting options as pattern recognition and predictions.

Definitely, the network slicing of 5G goes through the use of artificial intelligence and machine learning. Its use is revealed as the best way to optimize not only the management of telecommunications infrastructures but also the implementation processes through which we create the partitions.


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