Applications of machine learning to the planning of 5G-era small cell networks

Ever-growing demand for mobile data is driving network densification with the deployment of small cells. However, the identification of sites which can effectively capture traffic not served by the existing network is a complex optimisation problem that increasingly requires a computational approach. Here we consider the level of precision required in small cell planning and share two case studies of where machine learning techniques have been applied.

Subscribe to the CW newsletter

This site uses cookies.

We use cookies to help us to improve our site and they enable us to deliver the best possible service and customer experience. By clicking accept or continuing to use this site you are agreeing to our cookies policy. Learn more

Start typing and press enter or the magnifying glass to search

Sign up to our newsletter
Stay in touch with CW

Choosing to join an existing organisation means that you'll need to be approved before your registration is complete. You'll be notified by email when your request has been accepted.

Your password must be at least 8 characters long and contain at least 1 uppercase character, 1 lowercase character and at least 1 number.

I would like to subscribe to

Select at least one option*