TX-MAVENIR

Network Automation: Mavenir’s RAN Intelligent Controller (RIC) and Network Data Analytics Function (NWDAF) follow the specifications introduced by the O-RAN Alliance and 3GPP and operate as the heart of a network automation vision. The RIC and NWDAF enable the network to dynamically adapt to traffic conditions using machine learning (ML)-based algorithms and applications that can be deployed in any network in a multi-vendor environment. Mavenir’s containerized RIC and NWDAF product capabilities include:

• Non-RT RIC: designed to host advanced ML algorithms (rApps) to optimize network performance and train ML models using long-term RAN data for dynamic and adaptive policy for RAN performance optimization.
• Near-RT RIC: designed to host trained AI/ML models (xApps) to infer and control O-RAN functional elements in near-real time.
• NWDAF: designed to ingest data from 5G standalone (SA) network functions and to provide various analytics and intelligence services for smart network operation.

Intelligent Operations: By automating network operational processes with AI and analytics solutions, operators should be able to substantially reduce the cost and time from traditional, more labor-intensive methods such as drive testing, log inspection, troubleshooting, and manual calibration. With AI-based prediction engines, operators can achieve intelligent capacity planning and reduce the possibility of large-scale network outages. With anomaly detection capability, operators can uncover underlying network faults that are not easily visible. This AI-driven Operations (AIOps) solution using ML techniques plays a key role in reducing operating expenses and gives operators complete control over their networks.

5G EdgeAI : Mavenir’s 5G EdgeAI solution includes Intelligent Video Analytics that can support myriad of use cases from facial recognition to anomaly detection for smart city and industry 4.0 use cases. Next generation of AR/VR applications are accelerated and enhanced by this edge platform. Large number of sensor data gets analyzed and actions are taken in a matter of milliseconds by the edge Industrial Internet of Things (IIoT) analytics application.

“AI is the key driver for Industry 4.0, providing real-time insights & control of industrial processes. Low latency, high density of 5G are also enablers, so in essence, the combination of 5G and AI = Industry 4.0,” said Kuntal Chowdhury, SVP and GM, Mavenir AI and Analytics Business Unit. “While Mavenir’s AI and Analytics solutions are now available as standalone solutions, we have been offering intelligent insights as integrated solutions to Tier 1 customers around the world for years. Currently over 200 systems are deployed in more than 80 customer networks and our solutions process and analyze billions of records per day, offering real-time/near-real-time insights to optimize network performance with little to no human intervention.”

Network security: As new vulnerabilities arise, Mavenir’s Fraud Management and Security Suite protect the network in real-time with predictive analytics and ML. The Real-Time Fraud Management and Security analytics is leveraging unique ML algorithms and a specifically designed framework suited to manage the volume, velocity, and variety of structured and unstructured data over wireless networks.

“Mavenir Security and Anti-Fraud Solutions based on AI/ML are taking care of on-going revenue savings at Telefónica Argentina,” says Diego Quevedo, Core Network Solution Design Lead, Telefónica Argentina. “We are in close cooperation with Mavenir to ensure the up-to-date protection of our network.”

“Mavenir’s approach of applying Real-Time Machine Learning technology to protect key operator services and revenue has been highly valued by customers,” said Ilia Abramov, VP and GM, Mavenir Security BU. “New threats raised in the recent years and increasing attack vectors on Mobile Network Services have been successfully detected and blocked though our installed base. The increased level of trust of our AI/ML technology has been confirmed with substantial growth in additional network implementations in the last year.”