fresh support

Rice-led project receives $1.9M in federal funding to test 5G energy efficiency, more

The project will focus on testing 5G networks for "stability, interoperability, energy efficiency and communication performance." Photo via Getty Images

A team of Rice University engineers has secured a $1.9 million grant from the U.S. Department of Commerce’s National Telecommunications and Information Administration to develop a new way to test 5G networks.

The project will focus on testing 5G networks for software-centric architectures, according to a statement from Rice. The funds come from the NTIA's most recent round of grants, totaling about $80 million, as part of the $1.5 billion Public Wireless Supply Chain Innovation Fund. Other awards went to Virginia Tech, Northeastern University, DISH Wireless, and more.

The project at Rice will be led by Rahman Doost-Mohammady, an assistant research professor of electrical and computer engineering; and Ashutosh Sabharwal, the Ernest Dell Butcher Professor of Engineering and chair of the Department of Electrical and Computer Engineering. Santiago Segarra, assistant professor of electrical and computer engineering and an expert in machine learning for wireless network design, is also a co-principal investigator on this project.

"Current testing methodologies for wireless products have predominantly focused on the communication dimension, evaluating aspects such as load testing and channel emulation,” said Doost-Mohammady said in a statement. “But with the escalating trend toward software-based wireless products, it’s imperative that we take a more holistic approach to testing."

The new framework will be used to "assess the stability, interoperability, energy efficiency and communication performance of software-based machine learning-enabled 5G radio access networks (RANs)," according to Rice, known as ETHOS.

Once created, the team of researchers will use the framework for extensive testing using novel machine learning algorithms for 5G RAN with California-based NVIDIA's Aerial Research Cloud (ARC) platform. The team also plans to partner with other industry contacts in the future, according to Rice.

“The broader impacts of this project are far-reaching, with the potential to revolutionize software-based and machine learning-enabled wireless product testing by making it more comprehensive and responsive to the complexities of real-world network environments,” Sabharwal said in the statement. “By providing the industry with advanced tools to evaluate and ensure the stability, energy efficiency and throughput of their products, our research is poised to contribute to the successful deployment of 5G and beyond wireless networks.”

Late last year, the Houston location of Greentown Labs also landed funds from the Department of Commerce. The climatetech startup incubator was named to of the Economic Development Administration's 10th cohort of its Build to Scale program and will receive $400,000 with a $400,000 local match confirmed.

Houston-based nonprofit accelerator, BioWell, also received funding from the Build to Scale program.


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This article originally ran on InnovationMap.

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A View From HETI

SLB and NVIDIA plan to build an "AI factory for energy" to help the industry transform massive amounts of data into actionable information. Photo courtesy SLB

Houston-based energy technology company SLB has expanded its 18-year tech collaboration with chipmaker NVIDIA to include the development of an “AI factory for energy.”

Through their partnership, SLB and NVIDIA will create AI infrastructure and models built around SLB’s existing digital platforms to help energy companies scale AI for data and operations.

In addition to the development of the “AI factory,” SLB will:

  • Provide modular design services to enhance NVIDIA’s blueprint for building, launching and operating gigawatt-scale AI data centers. In this case, modular design involves manufacturing data center components off-site.
  • Use NVIDIA’s AI infrastructure to improve the processing of large datasets and AI models across SLB’s digital platforms.

Energy companies generate vast amounts of operational data, which can slow down and silo decision-making, SLB says. By combining NVIDIA’s Omniverse libraries and its Nemotron open models with SLB’s digital and AI platforms, the companies aim to more rapidly transform data into actionable insights.

Omniverse libraries are sets of prebuilt 3D elements, such as objects, surfaces and interactive features, that make it easier to construct detailed virtual spaces without having to design everything manually. They’re commonly used for building immersive environments, digital replicas of real-world systems and simulation scenarios.

Nemotron open models are AI models that are freely available to download and modify. Instead of relying on a hosted service, you can run them on your own infrastructure and tailor them to fit specific needs.

Vladimir Troy, vice president of AI infrastructure at NVIDIA, says the energy sector is at the forefront of AI driving a “new industrial revolution.”

“The winners in AI will be companies with the best data, the deepest domain expertise, and the ability to scale,” Demos Pafitis, SLB’s chief technology officer, added. “By collaborating with NVIDIA to advance modular data center construction and harness our domain expertise and digital platforms, we’re enabling the energy industry to deploy AI at scale and transform operational data into smarter decisions.”

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