This poll question was asked during a recent webinar 1 on using (RF) spectrum 2 in the era of 5G. “Compared with past Gs, how concerned are you about spectrum challenges in 5G?” Konstantinos holds a PhD in electrical and electronic engineering from Imperial College London, has presented at dozens of conferences and webinars, and has authored several articles, blogs and white papers on mobile networks. These solutions have supported automated planning/optimization, customer experience geolocation, device interoperability and acceptance testing, service assurance for physical/virtual networks, centralized and automated operations, and (big data) analytics.
#5g spectral efficiency software
His experience covers diverse areas, from antenna array systems research and mobile network planning/optimization consultancy to the development/management/marketing of innovative software solutions.
#5g spectral efficiency professional
Konstantinos has been focusing on mobile networks for more than 20 years, through academic and professional roles. In addition to EXFO’s 5G solutions and market positioning, he actively contributes to the promotion of EXFO’s solutions for automated operations and fiber monitoring. His main areas of focus are 5G, 4G evolution, network virtualization/transformation, analytics, and automation. Konstantinos Stavropoulos develops and executes the marketing strategy for EXFO's mobile network (access, core, end-to-end) monitoring/optimization solutions, which include intelligent software platforms and expert professional services. The €16bn Capgemini group has now integrated engineering group Altran that includes Cambridge Consultants, and has opened 5G R&D labs around Europe.Dr. 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,” said Cristina Rodriguez, VP of Wireless Access Network Division at Intel. “Our 3rd Gen Intel Xeon Scalable processors with built-in AI acceleration provide high performance for deep learning on the Net Anticipate 5G platform. This makes it cost efficient in the short run and future proof in the long run as we move into Cloud Native RAN implementations.” In short, machine learning can be deployed for intelligent decision-making on the RAN without any additional hardware requirement. “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. “Our teams worked closely with Intel to create a truly innovative solution that can really move the needle for operators,” said Walid Negm, Chief Research and Innovation Officer at Capgemini Engineering. The Capgemini ML software on the Intel Xeon increases the amount of traffic each cell can handle and allows more subscribers alongside new Industry 4.0 services such as enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communications (URLLC) use cases.
#5g spectral efficiency mac
In this way, the RAN can intelligently schedule MAC resources to achieve up to 40 percent more accurate MCS prediction which gives 15 percent better spectrum efficiency in testing. The project improved AI accuracy to 55 percent and reduced AI inference time to 0.64msec, a 41 percent improvement.
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. This is optimised for Intel’s AI Software and third generation Intel Xeon Scalable processors.Ĭapgemini used its NetAnticipate5G and RATIO OpenRAN platform to introduce advanced AI/ML techniques. Project Marconi uses the Open Radio Access Network OpenRAN guidelines to maximize spectrum efficiency with real-time predictive analytics in a 5G Mediua Access Control (MAC) schedule.
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