The Global AI Challenge

Last year, the GSMA announced selected four mobile network operators, STC, Telenor, TELUS and Turkcell, as challenge leaders, to take part in the first GSMA Global AI Challenge. The Challenge investigated three specific areas: connectivity in rural areas, mobile energy efficiency and enhanced services in urban areas.

The GSMA challenge is in partnership with The Alan Turing Institute, the UK national institute for data science and artificial intelligence. The Challenge brought together mobile network operators and universities’ artificial intelligence and data science departments to help solve challenging and complex real-world business problems.

The GSMA challenge was comprised of an intensive five-day hackathon and was a part of Turing’s Data Study Group (DSG). It is primarily focused on raising the profile of AI as a key enabler in the mobile industry and the transformational opportunities it provides, while also exploring how science, society and the economy might benefit.

The 4 study groups took place in September 2019 with initial results available at MWC Los Angeles 2019.

STC – Use AI to deliver high-speed bandwidth/high-speed connectivity in remote areas

Different mobile users have different bandwidth needs. Bandwidth availability usually depends on the user density in the targeted area. Reserving bandwidth is usually not desired in mobile networks as it is considered a waste of network resources. This DSG explored how mobile network operators can make available, the necessary bandwidth to specific urban or rural areas, which lag behind either because of high population density or lack of necessary infrastructure.

TELUS – Use AI and network data to improve and create new services in urban areas

TELUS frequently carries out surveys with its customers to gather feedback and identify requirements for service improvements to prioritize investments in a way that reflects their customers’ needs. This study group focused on understanding how the network and the customer experience (whilst using the network) influence the results of this survey.

More specifically, TELUS wanted to understand:

• How accurately the customer’s experience of reliability on their network can be predicted, and
• What are the main drivers of network performance to influence their customer’s rating of their experience?

Telenor – Use AI to improve energy efficiency in mobile networks

Mobile networks waste energy by keeping too many radio-cells switched on when the demand is low during off-peak times. This challenge was about automating next-day power saving schemes for each individual cell tower in a country, based on current load and expected demand profile in the area.  The solution should optimise power saved, while avoiding negative impact on the user’s network experience.

Turkcell – Use AI and network data to improve and create new services in urban areas

In urban areas, jammers can cause interruption on mobile 3G and 4G communication networks leading to severe service quality deterioration. This situation causes customer complaints and time and labour costs during detection studies. Based on network data including some network service quality indicators and jammer geographical location, this study group investigated methods for real-time detection of jammer presence, identification of jammer type and its location.