Machine learning research to advance future wireless networks
While current wireless networks support cellular and Wi-Fi services, future networks will need to support a much broader range of technologies, from driverless cars to remote health applications. The existing wireless spectrum is already over-congested, thanks to the explosion of network-connected devices that help people navigate their daily lives. As demand for capacity and coverage increases, expanding wireless spectrum is even more critical. Machine learning has emerged as a technique to potentially manage that growing complexity and scale while also improving the quality of service.
To catalyze development in this area, the U.S. National Science Foundation is partnering with Intel to fund research through the Machine Learning for Wireless Networking Systems program.
"The wireless networks of the future need to support much higher requirements than what current wireless networks can deliver, and they also need to be secure and energy-efficient," said Margaret Martonosi, assistant director for Computer and Information Science and Engineering. "That is why NSF and Intel have contributed $9 million to advance research activities addressing some of the most challenging issues in the development of future wireless systems."
This investment supports research to accelerate innovation and grows the number of workforce-ready STEM graduates. This fundamental, broad-based research on wireless-specific machine learning techniques enables new wireless architectures and systems for future applications.
"Since 2015, Intel and NSF have collectively contributed more than $30 million to support science and engineering research in emerging areas of technology. This program is the next step in this collaboration and has the promise to enable future wireless systems that serve the world's rising demand for pervasive, intelligent devices."
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