Ericsson and Nvidia virtualise 5G radio access networks
October 23, 2019
Ericsson and Nvidia are collaborating on technologies that can allow communication service providers to build virtualised 5G radio access networks (RANs). These virtualised networks can enable faster and more flexible introduction of AI and IoT services.
The collaboration brings together Ericsson's expertise in RAN technology with Nvidia's knowledge in graphics processing unit (GPU)-powered accelerated computing platforms, as well as AI and supercomputing.
Communication service providers are exploring alternative technologies and RAN architectures amid growing interest for virtualisation, while securing a better user experience.
A major industry challenge is how to virtualise the complete RAN in a cost-, size- and energy-efficient way, comparable with traditionally built RANs. The collaboration seeks to examine how these challenges can be addressed in a commercially viable way.
"As a technology leader, we embrace openness and new platforms where we can continue to innovate and push boundaries to provide our customers with the best possible solutions,” said Fredrik Jejdling, executive vice president at Ericsson. “With Nvidia we will jointly look at bringing alternatives to market for virtualising the complete radio access network."
The companies' goal is to commercialise virtualised RAN technologies to deliver radio networks with flexibility and shorter time to market for new services, such as augmented reality, virtual reality and gaming.
"5G is set to turbocharge the intelligent edge revolution,” said Jensen Huang, founder and chief executive officer of Nvidia. “Fusing 5G, supercomputing and AI has enabled us to create a revolutionary communications platform supporting, someday, trillions of always-on, AI-enabled smart devices. Combining our world-leading capabilities, Nvidia and Ericsson are helping to invent this exciting future."
Nvidia's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and changed parallel computing. More recently, GPU deep learning ignited modern AI with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world.