Machine Learning from Enea Openwave is Delivering 15% Increase in RAN Capacity

Enea Openwave announced that its RAN Congestion Manager (RCM) incorporating Machine Learning capabilities is increasing mobile operators’ 4G RAN capacity by 15% in congested locations. This has enabled Enea Openwave customers to cope with the double threat of increased data usage and a slowing down of 5G rollouts, brought on by the COVID-19 pandemic and resulting lockdowns globally. This has given operators’ 4G networks a new lease of life without any additional hardware investment.

According to multiple reports, many operators globally have slowed down the pace of their 5G network rollout, in the wake of COVID-19. This has forced a reassessment about how they can extract maximum value from their 4G network assets in the medium term. Also, during lockdowns, some operators faced a surge of over 90% in peak throughput, based on figures from Enea Openwave deployments worldwide.

8 out of 10 of the world's largest operator groups have now deployed Enea Openwave Traffic Management technology with a number of them upgrading to incorporate its Machine Learning capabilities, to enable optimal bandwidth utilization and improve 4G Quality of Experience (QoE). The Machine Learning capabilities dynamically predict and identify congestion in the RAN, enabling operators to take immediate remedial action.

While 5G can support up to 100 times more data traffic than 4G in the long-term, for the short to medium term, operators need to prolong 4G’s lifespan. A recent report from the GSMA confirms this trend and highlighted that 4G will in fact grow over the coming years, still accounting for 56 per cent of connections in 2025.

“Video streaming continues to experience high year on year growth and that has been exacerbated by the pandemic and resulting lock-downs”, commented Gorkem Yigit, Principal Analyst at Analysys Mason. “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.”

John Giere, President of Enea Openwave, said: “We have taken Machine Learning out of the lab and into commercial deployment. 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.”