Openwave Mobility Unveils Machine Learning Technology to Predict RAN Congestion and Reduce it by 20%

Machine Learning technology dynamically predicts localized congestion in the RAN, enabling operators to take selective policy action, with no RAN integration required

REDWOOD CITY, California – February 25th 2019Openwave Mobility, the market leader in mobile data traffic management solutions, today launched the Radio Access Network – Congestion Manager (RCM) for mobile operators to cut the number of congested cells by 20% and deliver outstanding video Quality of Experience (QoE) for subscribers.

The significant reduction in congestion is achieved thanks to machine learning technology, which dynamically detects and even predicts localized congestion at each network attachment point. RCM provides operators with an unparalleled view of congestion across the RAN, allowing network providers to take selective policy actions and boost subscriber QoE. Importantly, RCM requires no RAN integration.

Operators are struggling to manage RAN congestion and assure subscriber QoE. Mobile video traffic has grown at a phenomenal rate, and peaks are frequently unpredictable. High definition (HD), which requires up to 4x more bandwidth than standard video, and encrypted over-the-top (OTT) traffic compounds the problem even further.

Indranil Chatterjee, SVP of Products, Sales and Marketing said: “Existing solutions from other vendors require manual configuration of static values, such as peak times or congested cells, or in some cases require external RAN probes. Our machine learning-based solution dynamically determines congested traffic and radio network locations, optimizing only the necessary traffic.”

Chatterjee continued: “Our solution works across traffic from all RAN vendors, across all spectrums, without the need for external probes or changes to the operator’s RAN. This leads to significant operational simplicity. Operators need RCM to handle the ongoing tsunami of data, and early customer results have seen a 20% drop in congested cells during peak hours.”

RCM is easy to deploy without probes or RAN or packet core integration. The fully automated system monitors IP packets on the data plane and gives a complete view of congestion in the network via the RCM Dashboard. Thus, it precisely predicts congested locations, enabling video optimization technology to balance radio resources across users and deliver fair and consistent video quality to all users.

Visit Openwave Mobility at Mobile World Congress 2019: Booth 7A11 or visit the ENEA booth: 6G10.

About Openwave Mobility
Openwave Mobility, an Enea company, empowers mobile operators to manage and monetize encrypted traffic. Based on the industry’s most scalable NFV platform, our solutions alleviate RAN congestion, create new revenue opportunities and unify subscriber data. The company provides solutions for mobile video traffic management, cloud data management and targeted promotions.

About Enea
Enea develops the software foundation for the connected society. We provide solutions for mobile traffic optimization, subscriber data management, network virtualization, traffic classification, embedded operating systems, and professional services. Solution vendors, systems integrators, and service providers use Enea to create new world-leading networking products and services. More than 3 billion people around the globe already rely on Enea technologies in their daily lives. Enea is listed on Nasdaq Stockholm. For more information: www.enea.com

For further information
For APAC and EMEA Inquiries:
Chevaan Seresinhe
Sonus PR
chevaan.seresinhe@sonuspr.com
Tel: +44 797 1967 644

For Americas Inquiries
Micah Warren
micah.warren@sonuspr.com
Tel: +1 (609) 247-6525

Syndicated from http://www.realwire.com/releases/Openwave-Mobility-Unveils-Machine-Learning-Technology

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