Webinar on Demand: How to Effectively Use the Potential of 5G: Network Slicing and the Role of AI and Machine Learning
- Published
- 4 min reading
The emergence of 5G creates unprecedented potential for communication service providers to generate and deliver new services and experiences for their customers. It’s not just a promise of faster and more efficient network – it’s a revolution for the way networks are managed and an opportunity to provide new types of services. But, in order to fully utilize the potential of 5G, telecoms need to prepare their networks and businesses for the big change.
Can network slicing combined with AI and ML help them reach the goal?
Network slicing – the real 5G enabler
CSPs need to adjust their networks and organizations to the new requirements set by 5G technology. It is important to understand that 5G networks can serve CSPs’ customers for many various purposes, such as mobile, automotive and more. This means that a network based on a single physical infrastructure needs to meet the very different needs of customers. 5G network slicing can help operators to do this seamlessly.
What is 5G network slicing?
The concept of network slicing is to enable the rapid (on demand even) creation of logical/virtual networks based on one physical technical infrastructure. It works by creating “dedicated” networks that can serve different objectives or even partners. So, instead of having a jammed network that needs to provide the service for all the different purposes, a CSP is able to divide it into smaller slices that are each dedicated to specific tasks.
5G network slicing gives the operator efficiency, flexibility, and more agility to address customers’ needs. But implementation depends on the telecom environment. In some cases it can be a very smooth process, while in others it takes time and will involve changes to the network – as 5G network slicing does mean significant complications in network management.
AI and ML in the service of network slicing
Applying artificial intelligence and machine learning is crucial for ensuring that network slicing functions correctly. AI-driven solutions bring agility and flexibility to the arrangement, making it possible for network slicing to work seamlessly. Automation can help in managing applications by providing solutions such as pattern recognition, predictions, and so on.
If you’d like to learn more about network slicing and the role of AI and ML in effective utilization of 5G, watch our webinar on demand: “How to Effectively Use the Potential of 5G: Network Slicing and the Role of AI and Machine Learning”.
In the video, our expert provides you with information on:
• What exactly network slicing means
• When it can be applied
• What role artificial intelligence and machine learning can play in network slicing
• How to implement AI and ML to automate network and application management
