Enea Openwave, which provides solutions to mobile operators for video traffic management and 5G data management, has announced that its RAN Congestion Manager (RCM) incorporating machine learning capabilities is increasing mobile operators’ 4G RAN capacity by 15% in congested locations.
Such capability is crucial in today's video market said Gorkem Yigit, principal analyst at Analysys Mason. “Video streaming continues to experience high year on year growth and that has been exacerbated by the pandemic and resulting lockdowns," he observed. ".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 maximise and extend existing 4G network capabilities in the short to medium term - keeping their CAPEX to a minimum.”
The Covid pandemic has seen increased data usage worldwide together with a slowdown in 5G network rollouts, and Enea says RCM has enabled mobile operators to give their 4G networks a new lease of life without any additional hardware investment.
Enea Openwave says 8 out of 10 of the world's largest operator groups have now deployed its traffic management technology with a number upgrading to incorporate its machine learning capabilities, to enable optimal bandwidth utilisation 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 highlights that 4G will in fact grow over the coming years, still accounting for 56% of connections in 2025.
“We have taken machine learning out of the lab and into commercial deployment," remarked John Giere, president of Enea Openwave. "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.”