NVIDIA 6G Developer Day 2024 brought together members of the 6G research and development community to share insights and learn new ways of engaging with NVIDIA 6G research tools. More than 1,300 academic and industry researchers from across the world attended the virtual event. It featured presentations from NVIDIA, ETH Z��rich, Keysight, Northeastern University, Samsung, Softbank��
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The pace of 6G research and development is picking up as the 5G era crosses the midpoint of the decade-long cellular generation time frame. In this blog post, we highlight how NVIDIA is playing an active role in the emerging 6G field, enabling innovation and fostering collaboration in the industry. NVIDIA is not only delivering AI native 6G tools but is also working with partners and��
]]>6G will make the telco network AI-native for the first time. To develop 6G technologies, the telecom industry needs a whole new approach to research. The world of wireless communication is on the verge of a major transformation with the advent of 6G technology. 6G, the upcoming sixth-generation wireless network, is expected to provide extremely high-performance interconnections��
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In 3GPP fifth generation (5G) cellular standard, layer 1 (L1) or the physical layer (PHY) is the most compute-intensive part of the radio access network (RAN) workload. It involves some of the most complex mathematical operations with sophisticated algorithms like channel estimation and equalization, modulation/demodulation, and forward error correction (FEC). These functions require high compute��
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Wireless technology has evolved rapidly and the 5G deployments have made good progress around the world. Up until recently, wireless RAN was deployed using closed-box appliance solutions by traditional RAN vendors. This closed-box approach is not scalable, underuses the infrastructure, and does not deliver optimal RAN TCO. It has many shortcomings. We have come to realize that such closed-box��
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The pace of 5G investment and adoption is accelerating. According to the GSMA Mobile Economy 2023 report, nearly $1.4 trillion will be spent on 5G CapEx, between 2023 and 2030. Radio access network (RAN) may account for over 60% of the spend. Increasingly, the CapEx spend is moving from the traditional approach with proprietary hardware, to virtualized RAN (vRAN) and Open RAN architectures��
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NVIDIA introduced Aerial Research Cloud, the first fully programmable 5G and 6G network research sandbox, which enables researchers to rapidly simulate, prototype, and benchmark innovative new software deployed through over-the-air networks. The platform democratizes 6G innovations with a full-stack, C-programmable 5G network, and jumpstarts ML in advanced wireless communications using NVIDIA��
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The role of artificial intelligence (AI) in boosting performance and energy efficiency in cellular network operations is rapidly becoming clear. This is especially the case for radio access networks (RANs), which account for over 60% of industry costs. This post explains how AI is transforming the 5G RAN, improving energy and cost efficiency while supporting better use of RAN computing��
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The cellular industry spends over $50 billion on radio access networks (RAN) annually, according to a recent GSMA report on the mobile economy. Dedicated and overprovisioned hardware is primarily used to provide capacity for peak demand. As a result, most RAN sites have an average utilization below 25%. This has been the industry reality for years as technology evolved from 2G to 4G.
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Virtualization is key to making networks flexible and data processing faster, better, and highly adaptive with network infrastructure from Core to RAN. You can achieve flexibility in deploying 5G services on commercial off-the-shelf (COTS) systems. However, 5G networks bring support for ultra-low latency, high-bandwidth applications, and scalable networks with network slicing and software��
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