Capgemini’s Project Marconi to Boost Spectrum Efficiency
Capgemini has released a breakthrough solution giving mobile operators a significant advantage to monetize 5G services faster. Entitled “Project Marconi”, the solution conforms to O-RAN (Open Radio Access Network) guidelines to maximize spectrum efficiency.
Walid Negm, Chief Research and Innovation Officer at Capgemini Engineering said: “Our teams worked closely with Intel to create a truly innovative solution that can move the needle for operators. We gathered and utilized over one terabyte of data and conducted countless test runs with NetAnticipate5G to fine-tune the predictive analytics to meet diverse operator requirements. In short, machine learning can be deployed for intelligent decision-making on the RAN without any additional hardware required. This makes it cost-efficient in the short run and future proof in the long run as we move into Cloud Native RAN implementations.”
Cristina Rodriguez, VP of Wireless Access Network Division at Intel said: “Our 3rd Gen Intel Xeon Scalable processors with built-in AI acceleration provide high performance for deep learning on the Net Anticipate 5G platform. Together, our collaboration delivered ultra-fast inference data to enhance the Open-Source ML libraries resulting in an intelligent RAN that can predict and quickly react to subscriber coverage requirements while reducing TCO.”
The solution intelligently boosts subscriber quality of experience (QoE) with real-time predictive analytics.
Project Marconi is the industry’s first Artificial Intelligence / Machine Learning (AI/ML) based radio network application for 5G Medium Access Control (MAC) scheduler. Optimized with Intel AI Software and 3rd Gen Intel Xeon Scalable processors.
Capgemini Project Marconi solution on Intel Architecture increases the amount of traffic each cell can handle. It allows operators to serve more subscribers and deliver an outstanding experience while launching new Industry 4.0 services such as enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC) use cases.
Capgemini deployed its NetAnticipate5G and RATIO O-RAN platform to introduce advanced AI/ML techniques. The AI-powered predictive analytical solution forecasts and assigns the appropriate MCS (modulation and coding scheme) values for signal transmission through forecasting of the user signal quality and mobility patterns accurately.
In this way, the RAN can intelligently schedule MAC resources to achieve up to 40% more accurate MCS prediction and yield to 15% better spectrum efficiency in the case studies and testing.
