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NIST aims to make frequency sharing more efficient for wireless networks

A machine-learning formula developed by the National Institute of Standards and Technology (NIST) has the potential to significantly improve how 5G and other wireless networks select and share communications frequencies. Compared to trial-and-error methods, NIST’s formula could make the process of sharing communications frequencies as much as 5,000 times more efficient, researchers claim.

The NIST system is based the idea that radio equipment can learn its network environments from experience rather than, as is done now, simply select frequency channels based on trial-and-error.

“The algorithm learns which channel provides the best outcome” under specific environmental conditions, NIST says in an article on its website.

“The formula could be programmed into software on transmitters in many [different] types of real-world networks,” the team says.

Essentially, the computer-modeled algorithm is a formula that maps prior experience in environmental RF conditions. Those conditions can include the number of transmitters operating within a channel (set of adjacent frequencies), for example.

“… if a transmitter selects a channel that is not occupied, then the probability of a successful transmission rises, leading to a higher data rate,” the article says. Likewise, when a transmitter selects a channel that doesn’t have much interference on it, the signal is stronger, and you get a better data rate. The transmitter remembers which channel provides the best outcome and learns to choose that spot on the dial when it next needs a clear signal.

Copyright © 2020 IDG Communications, Inc.

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