Ericsson launches smarter networks that learn and improve

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Ericsson has announced the debut of its Network Data Analytics Function (NWDAF) solution, which is built on smarter data-driven networks that learn and improve. Ericsson’s NWDAF helps service providers improve customer experience by utilising network data to identify and resolve issues, enhancing service quality.

Neil McRae, MD Architecture & Strategy, BT Group Chief Architect, says: “At BT we connect for good and our customers increasing reliance on the network requires us to think differently. With Ericsson, we are working on cloud-native solutions for 5G Core architecture to support multiple generations of technologies.”

He added, “we see the need for greater automation and analytics to manage complex networks and ensure the best quality experience for our customers. I’m pleased to see that Ericsson is launching NWDAF, building upon Ericsson’s built-in software probes and Expert Analytics (EEA), a natural next step development to enhance closed-loop automation and service assurance that could benefit BT’s Customer Network Experience (CNE) platform.”

Monica Zethzon, Head of Solution Area Packet Core, Ericsson, says: “Everything 5G, especially 5G Core networks, must be automated. Automation will improve operational efficiency, reduce time to market for new services, and handle the magnitude of tailor-made services introduced with 5G. With the launch of NWDAF, we build the automated closed-loop and assurance, enabled by AI and machine learning, to leverage data-driven operation based on network data.”

James Crawshaw, Principal Analyst, Telco IT & Operations, Omdia, says: “Ericsson’s NWDAF adds intelligence to the 5G core, bringing new insights that enable automation and optimization. With this solution, Ericsson shows its technology leadership in 5G Core.”

Automating certain basic and complex operations to enable zero-touch autonomous networking, which necessitates the use of advanced technologies such as artificial intelligence (AI), machine learning (ML), and reasoning, is a continual undertaking for 5G. NDWAF accomplishes this by obtaining the appropriate data at the appropriate cost for use in AI/ML models.

NWDAF improves network operability by providing information that assists the service provider in identifying and resolving network issues at various levels and input for making important business choices. Automated closed loops (data retrieval, analytics processing, insight production, and action enforcement) provide one example on many network and application levels.

When compared to a typical third-party NWDAF deployment with event exposure, Ericsson’s NWDAF can save up to 45 percent on OPEX and CAPEX. Smart data capture facilitates faster integration and testing, as well as easier orchestration and a smaller footprint.

Ericsson’s cloud-native dual-mode 5G Core and Ericsson Expert Analytics both use NWDAF as a reusable set of microservices. Thanks to its flexible deployment scenarios and model portability, the NWDAF may be deployed centrally and as a built-in NWDAF in 5G Core products. The NWDAF is based on 3GPP Release 17, which defines a distributed network analytics architecture with independent inference and training and a data repository.


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