• Ericsson to supply Artificial Intelligence (AI) Performance Diagnostic solution
• Solution to apply machine learning and deliver performance insights
• Solution will provide analytics and recommendation to NTT DOCOMO to optimize its nationwide RAN
Ericsson (NASDAQ: ERIC) has been selected by Japanese communications service provider NTT DOCOMO as its AI-based optimization solution vendor for its nationwide radio access network (RAN).
The companies have been collaborating on introducing new solutions for decades, recently focusing on 5G proof of concept activities. The AI-based Performance Diagnostic solution for RAN optimization is one such effort and result of this collaboration.
Leveraging on Ericsson's global knowledge and experience, and collaborating with NTT DOCOMO's network optimization expertise, the AI-based Performance Diagnostic solution will apply innovative machine learning and complex problem-solving techniques to classify cell performance issues and recommend changes. NTT DOCOMO's planning and optimization teams will be able to evaluate the solution's output to expedite optimization efforts accurately and in a timely manner.
The companies conducted trials in 12 cities. The Ericsson Performance Diagnostics solution achieved 98% accuracy in classifying performance issues. The commercial operation to cover nationwide network is planned for March 2020.
Hozumi Tamura, Executive Vice President, NTT DOCOMO, says: “NTT DOCOMO has proactively worked on service area expansion and communication quality improvement in an effort to provide comfortable communication areas to our customers. Leveraging AI and our know-how that has been developed for years, we will further improve network quality.”
Peter Laurin, Executive Vice President and Head of Business Area Managed Service, Ericsson, says: “Close collaboration with NTT DOCOMO highlights the real benefits and value that AI-based and machine leaning solutions can bring to communications service providers' network operations. This solution maximizes end-user experience in service provider's networks while minimizing their total cost of ownership.”