One of the challenges of designing 5G networks is that they will have many different users, each with very different needs.
Imagine: people might be making video phone calls or streaming YouTube videos, whilst receiving a shopping list from the smart fridge and driving a smart car that’s communicating with other cars and the surrounding traffic lights, all of which are communicating via the 5G network. How can we process all of these requests for data? This is the main problem that the Wu Lab team are trying to tackle in this stream of research.
Watch the video and have a look through the infographic below to understand more, and read some of the recent paper summaries to understand the progress so far.
In our first YouTube video, we give an introduction to this research, and hear from Dr Wu and Dr Wang about how they are using AI and machine learning techniques to improve network slicing.
To understand more about what network slicing is, and how AI and machine learning can help, check out our infographic:
Network Slicing: Recent Paper Summaries
We’ve published a number of academic papers on the topic of network slicing. Here you can find some simple explanations of our recent papers – why network slicing is important and how AI & machine learning are useful in sharing out resources in the network. We also compare the difficulty of sharing out resources in a constantly changing network to weather forecasting!
Network Slicing: Outreach Activities
We’ve been working with the Exeter Mathematics School students on mini-projects related to our work. Have a look at our outreach page to learn more!