Artificial intelligence is helping telecoms operators to boost the RAN capacity of their 4G networks by 15 percent.
More people than ever are relying on telecoms networks to work, play, and stay connected during the pandemic. Operators are doing all they can to ensure their existing networks have enough capacity to cope with demand.
Gorkem Yigit, Principal Analyst at Analysys Mason, said:
“Video streaming continues to experience high year on year growth and that has been exacerbated by the pandemic and resulting lock-downs,
Yes, 5G grabs the spotlight, but 4G is carrying the brunt of this traffic. So, while investment in 5G infrastructure continues, operators need intelligent ways to maximize and extend existing 4G network capabilities in the short to medium term – keeping their CAPEX to a minimum.”
8 out of 10 of the world’s largest operator groups have deployed traffic management technology from the Openwave subsidiary of Swedish firm Enea. Many of these have since upgraded to include machine learning capabilities.
Openwave claims that, based on its figures, some operators faced a 90 percent surge in peak throughput during lockdowns.
Machine learning is helping to predict and identify congestion in the RAN (Radio Access Network) which resides between user equipment such as wireless devices and an operator’s core network.
John Giere, President of Enea Openwave, commented:
“Conventional mobile data management requires manual configuration and network investment – it is no longer fit for purpose.
Machine Learning has given existing 4G networks the shot in the arm they needed. It can work dynamically without external probes or changes to the RAN, delivering additional capacity at a time that operators most need it.”
The use of machine learning has increased operators’ 4G RAN capacity by 15 percent in congested locations—providing further evidence of how AI technology can be used to quickly tackle real-world problems.