Machine Learning-Based RAN Application Boosts Spectral Efficiency
July 01, 2021
Capgemini announced a solution designed to offer mobile operators an advantage to monetize 5G services quicker.
Entitled “Project Marconi”, the solution conforms to O-RAN (Open Radio Access Network) guidelines to maximize spectrum efficiency. The solution is designed to increase subscriber quality of experience (QoE) with real-time predictive analytics.
According to the comapny, 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.
According to the Global Mobile Suppliers Association, the total value of spectrum auctions reached over $27 billion in 2020. Capgemini’s solution on Intel Architecture is designed to increase the amount of traffic each cell can handle. It allows operators to serve more subscribers and deliver an ideal 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. Per the company, 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. As a result, it delivers ideal data speeds, and ideal QoE to subscribers and coverage for use cases that rely on low latency connectivity such as robotics-based manufacturing and V2X (vehicle-to-everything).
For more information, visit: www.capgemini.com